subject:(logistic regression)

University of Pretoria

1. Matshego, James Moeng. The variable selection problem and the application of the roc curve for binary outcome variables.

Degree: Statistics, 2008, University of Pretoria

URL: http://hdl.handle.net/2263/27133

► Variable selection refers to the problem of selecting input variables that are most predictive of a given outcome. Variable selection problems are found in all… (more)

▼ Variable selection refers to the problem of selecting input variables that are most predictive of a given outcome. Variable selection problems are found in all machine learning tasks, supervised or unsupervised, classification, regression, time series prediction , two - class or multi-class, posing various levels of challenges. Variables selection problems are related to the problems of input dimensionality reduction and of parameter planning. It has practical and theoretical challenges of its own. From the practical point of view, eliminating variables may reduce the cost of producing the outcome and increase its speed, while space dimensionality does not address these problems. Theoretical challenges include estimating with what confidence one can state that a variable is relevant to the concept when it is useful to the outcome and providing a theoretical understanding of the stability of selected variables subsets. As the probability cut-points increase in value, the more likely it becomes that an observation is classified as a non-event by the selected variables. The mathematical statement of the problem is not widely agreed upon and may depend on the application. One typically distinguishes: i) The problem of discovering all the variables relevant to the outcome variable and determine HOW relevant they are and how they are related to each other. ii) The problem of finding a minimum subset of variables that is useful to the outcome variable. Logistic regression is an increasingly popular statistical technique used to model the probability of discrete binary outcome. Logistic regression applies maximum likelihood estimation after transforming the outcome variable into a logit variable. In this way, logistic regression estimates the probability of a certain event. When properly applied, logistic regression analyses yield a very powerful insight in to what variables are more or less likely to predict event outcome in a population of interest. These models also show the extent to which changes in the values of the variable may increase or decrease the predicted probability of event outcome. Variable selection, in all its facets is similarly important with logistic regression. The receiver operating characteristics (ROC) curve is a graphic display that gives a measure of the predictive accuracy of a logistic regression model. It is a measure of classification performance, the area under the ROC curve (AUC) is a scalar measure gauging one facet of performance. Another measure of predictive accuracy of a logistic regression model is a classification table. It uses the model to classifying observations as events if their estimated probability is greater or equal to a given probability cut-point, otherwise events are classified as non-events. This technique, as it appears in the literature, is also studied in this thesis. In this thesis the issue of variable selection, both for continuous and binary outcome variables, is investigated as it appears in the statistical literature. It is clear that this topic has been widely… Advisors/Committee Members: Prof H T Groeneveld (advisor), Prof A J van der Merwe (advisor).

Subjects/Keywords: Logistic regression; Parameter planning; UCTD

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Matshego, J. (2008). The variable selection problem and the application of the roc curve for binary outcome variables. (Masters Thesis). University of Pretoria. Retrieved from http://hdl.handle.net/2263/27133

Chicago Manual of Style (16^th Edition):

Matshego, James. “The variable selection problem and the application of the roc curve for binary outcome variables.” 2008. Masters Thesis, University of Pretoria. Accessed February 21, 2020. http://hdl.handle.net/2263/27133.

MLA Handbook (7^th Edition):

Matshego, James. “The variable selection problem and the application of the roc curve for binary outcome variables.” 2008. Web. 21 Feb 2020.

Vancouver:

Matshego J. The variable selection problem and the application of the roc curve for binary outcome variables. [Internet] [Masters thesis]. University of Pretoria; 2008. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/2263/27133.

Council of Science Editors:

Matshego J. The variable selection problem and the application of the roc curve for binary outcome variables. [Masters Thesis]. University of Pretoria; 2008. Available from: http://hdl.handle.net/2263/27133

Texas A&M University

2. Sun, Chih-Chen. Modeling and characterization of potato quality by active thermography.

Degree: 2009, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-3012

► This research focuses on characterizing a potato with extra sugar content and identifying the location and depth of the extra sugar content using the active… (more)

Subjects/Keywords: thermography; logistic regression model; potato

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APA (6^th Edition):

Sun, C. (2009). Modeling and characterization of potato quality by active thermography. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-3012

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sun, Chih-Chen. “Modeling and characterization of potato quality by active thermography.” 2009. Thesis, Texas A&M University. Accessed February 21, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-3012.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sun, Chih-Chen. “Modeling and characterization of potato quality by active thermography.” 2009. Web. 21 Feb 2020.

Vancouver:

Sun C. Modeling and characterization of potato quality by active thermography. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3012.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sun C. Modeling and characterization of potato quality by active thermography. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3012

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

3. Borg, Kyle. Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow.

Degree: 2010, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7653

► The relationship between precipitation and large-flow is important to understand and characterize in the climate system. We examine statistical relationships between the Tropical Rainfall Measurement… (more)

▼ The relationship between precipitation and large-flow is important to understand and characterize in the climate system. We examine statistical relationships between the Tropical Rainfall Measurement Mission (TRMM) 3B42 gridded precipitation and large-scale ow variables in the Tropics for 2000{2007. These variables include NCEP/NCAR Re-analysis sea surface temperatures (SSTs), vertical temperature pro files, omega, and moist static energy, as well as Atmospheric Infrared Sounder (AIRS) vertical temperatures and QuikSCAT surface divergence. We perform correlation analysis, empirical orthogonal function analysis, and logistic regression analysis on monthly, pentad, daily and near-instantaneous time scales. Logistic regression analysis is able to incorporate the non-linear nature of precipitation in the relation- ship. Flow variables are interpolated to the 0.25 degrees TRMM 3B42 grid and examined separately for each month to o set the effects of the seasonal cycle. January correlations of NCEP/NCAR Re-analysis SSTs and TRMM 3B42 precipitation have a coherent area of positive correlations in the Western and Central Tropical Pacific on all time scales. These areas correspond with the South Pacific Convergence Zone (SPCZ) and the Inter Tropical Convergence Zone (ITCZ). 500mb omega is negatively correlated with TRMM 3B42 precipitation across the Tropics on all time scales. QuikSCAT divergence correlations with precipitation have a band of weak and noisy correlations along the ITCZ on monthly time scales in January. Moist static energy, calculated from NCEP/NCAR Re-analysis has a large area of negative correlations with precipitation in the Central Tropical Pacific on all four time scales. The first few Empirical Orthogonal Functions (EOFs) of vertical temperature profiles in the Tropical Pacific have similar structure on monthly, pentad, and daily timescales. Logistic regression fit coefficients are large for SST and precipitation in four regions located across the Tropical Pacific. These areas show clear thresholded behavior. Logistic regression results for other variables and precipitation are less clear. The results from SST and precipitation logistic regression analysis indicate the potential usefulness of logistic regression as a non-linear statistic relating precipitation and certain ow variables. Advisors/Committee Members: Saravanan, R. (advisor), Bowman, Kenneth (committee member), Jun, Mikyoung (committee member).

Subjects/Keywords: climate; logistic regression; TRMM precipitation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Borg, K. (2010). Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7653

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Borg, Kyle. “Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow.” 2010. Thesis, Texas A&M University. Accessed February 21, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7653.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Borg, Kyle. “Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow.” 2010. Web. 21 Feb 2020.

Vancouver:

Borg K. Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7653.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Borg K. Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7653

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Georgia

4. Tan, Xiaoyan. Analysis of toxcast phase ii data-predicting in vivo toxicities from in vitro data using optimal models.

Degree: MS, Biostatistics, 2017, University of Georgia

URL: http://hdl.handle.net/10724/38087

► Considering traditional animal-based testing approaches are expensive and time-consuming, the application of in vitro testing to predict patterns of toxicity was highlighted, ToxCast program was… (more)

Subjects/Keywords: ToxCast; SVM; logistic regression; CART

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APA (6^th Edition):

Tan, X. (2017). Analysis of toxcast phase ii data-predicting in vivo toxicities from in vitro data using optimal models. (Masters Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/38087

Chicago Manual of Style (16^th Edition):

Tan, Xiaoyan. “Analysis of toxcast phase ii data-predicting in vivo toxicities from in vitro data using optimal models.” 2017. Masters Thesis, University of Georgia. Accessed February 21, 2020. http://hdl.handle.net/10724/38087.

MLA Handbook (7^th Edition):

Tan, Xiaoyan. “Analysis of toxcast phase ii data-predicting in vivo toxicities from in vitro data using optimal models.” 2017. Web. 21 Feb 2020.

Vancouver:

Tan X. Analysis of toxcast phase ii data-predicting in vivo toxicities from in vitro data using optimal models. [Internet] [Masters thesis]. University of Georgia; 2017. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10724/38087.

Council of Science Editors:

Tan X. Analysis of toxcast phase ii data-predicting in vivo toxicities from in vitro data using optimal models. [Masters Thesis]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/38087

Duquesne University

5. Nelson, Bryan. Modeling the NCAA Tournament Through Bayesian Logistic Regression.

Degree: MS, Computational Mathematics, 2012, Duquesne University

URL: https://dsc.duq.edu/etd/970

► Many rating systems exist that order the Division I teams in Men's College Basketball that compete in the NCAA Tournament, such as seeding teams on… (more)

Subjects/Keywords: Bayesian; Logistic regression; MCMC; NCAA

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Nelson, B. (2012). Modeling the NCAA Tournament Through Bayesian Logistic Regression. (Masters Thesis). Duquesne University. Retrieved from https://dsc.duq.edu/etd/970

Chicago Manual of Style (16^th Edition):

Nelson, Bryan. “Modeling the NCAA Tournament Through Bayesian Logistic Regression.” 2012. Masters Thesis, Duquesne University. Accessed February 21, 2020. https://dsc.duq.edu/etd/970.

MLA Handbook (7^th Edition):

Nelson, Bryan. “Modeling the NCAA Tournament Through Bayesian Logistic Regression.” 2012. Web. 21 Feb 2020.

Vancouver:

Nelson B. Modeling the NCAA Tournament Through Bayesian Logistic Regression. [Internet] [Masters thesis]. Duquesne University; 2012. [cited 2020 Feb 21]. Available from: https://dsc.duq.edu/etd/970.

Council of Science Editors:

Nelson B. Modeling the NCAA Tournament Through Bayesian Logistic Regression. [Masters Thesis]. Duquesne University; 2012. Available from: https://dsc.duq.edu/etd/970

University of Pretoria

6. [No author]. The variable selection problem and the application of the roc curve for binary outcome variables .

Degree: 2008, University of Pretoria

URL: http://upetd.up.ac.za/thesis/available/etd-08112008-104847/

► Variable selection refers to the problem of selecting input variables that are most predictive of a given outcome. Variable selection problems are found in all… (more)

▼ Variable selection refers to the problem of selecting input variables that are most predictive of a given outcome. Variable selection problems are found in all machine learning tasks, supervised or unsupervised, classification, regression, time series prediction , two - class or multi-class, posing various levels of challenges. Variables selection problems are related to the problems of input dimensionality reduction and of parameter planning. It has practical and theoretical challenges of its own. From the practical point of view, eliminating variables may reduce the cost of producing the outcome and increase its speed, while space dimensionality does not address these problems. Theoretical challenges include estimating with what confidence one can state that a variable is relevant to the concept when it is useful to the outcome and providing a theoretical understanding of the stability of selected variables subsets. As the probability cut-points increase in value, the more likely it becomes that an observation is classified as a non-event by the selected variables. The mathematical statement of the problem is not widely agreed upon and may depend on the application. One typically distinguishes: i) The problem of discovering all the variables relevant to the outcome variable and determine HOW relevant they are and how they are related to each other. ii) The problem of finding a minimum subset of variables that is useful to the outcome variable. Logistic regression is an increasingly popular statistical technique used to model the probability of discrete binary outcome. Logistic regression applies maximum likelihood estimation after transforming the outcome variable into a logit variable. In this way, logistic regression estimates the probability of a certain event. When properly applied, logistic regression analyses yield a very powerful insight in to what variables are more or less likely to predict event outcome in a population of interest. These models also show the extent to which changes in the values of the variable may increase or decrease the predicted probability of event outcome. Variable selection, in all its facets is similarly important with logistic regression. The receiver operating characteristics (ROC) curve is a graphic display that gives a measure of the predictive accuracy of a logistic regression model. It is a measure of classification performance, the area under the ROC curve (AUC) is a scalar measure gauging one facet of performance. Another measure of predictive accuracy of a logistic regression model is a classification table. It uses the model to classifying observations as events if their estimated probability is greater or equal to a given probability cut-point, otherwise events are classified as non-events. This technique, as it appears in the literature, is also studied in this thesis. In this thesis the issue of variable selection, both for continuous and binary outcome variables, is investigated as it appears in the statistical literature. It is clear that this topic has been widely… Advisors/Committee Members: Prof H T Groeneveld (advisor), Prof A J van der Merwe (advisor).

Subjects/Keywords: Logistic regression; Parameter planning; UCTD

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

author], [. (2008). The variable selection problem and the application of the roc curve for binary outcome variables . (Masters Thesis). University of Pretoria. Retrieved from http://upetd.up.ac.za/thesis/available/etd-08112008-104847/

Chicago Manual of Style (16^th Edition):

author], [No. “The variable selection problem and the application of the roc curve for binary outcome variables .” 2008. Masters Thesis, University of Pretoria. Accessed February 21, 2020. http://upetd.up.ac.za/thesis/available/etd-08112008-104847/.

MLA Handbook (7^th Edition):

author], [No. “The variable selection problem and the application of the roc curve for binary outcome variables .” 2008. Web. 21 Feb 2020.

Vancouver:

author] [. The variable selection problem and the application of the roc curve for binary outcome variables . [Internet] [Masters thesis]. University of Pretoria; 2008. [cited 2020 Feb 21]. Available from: http://upetd.up.ac.za/thesis/available/etd-08112008-104847/.

Council of Science Editors:

author] [. The variable selection problem and the application of the roc curve for binary outcome variables . [Masters Thesis]. University of Pretoria; 2008. Available from: http://upetd.up.ac.za/thesis/available/etd-08112008-104847/

Humboldt State University

7. Barnes, Jason M. A sociospatial model to predict the success of entrepreneurs in Mendocino County, California.

Degree: MS, Natural Resources: Natural Resources Planning and Interpretation, 2012, Humboldt State University

URL: http://hdl.handle.net/2148/1257

► Predicting business success in rural areas solely on spatial characteristics is virtually nonexistent in literature. In this study I used logistic regression, geographical information systems… (more)

Subjects/Keywords: Sociospatial; GIS; Prediction; Logistic regression

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APA (6^th Edition):

Barnes, J. M. (2012). A sociospatial model to predict the success of entrepreneurs in Mendocino County, California. (Masters Thesis). Humboldt State University. Retrieved from http://hdl.handle.net/2148/1257

Chicago Manual of Style (16^th Edition):

Barnes, Jason M. “A sociospatial model to predict the success of entrepreneurs in Mendocino County, California.” 2012. Masters Thesis, Humboldt State University. Accessed February 21, 2020. http://hdl.handle.net/2148/1257.

MLA Handbook (7^th Edition):

Barnes, Jason M. “A sociospatial model to predict the success of entrepreneurs in Mendocino County, California.” 2012. Web. 21 Feb 2020.

Vancouver:

Barnes JM. A sociospatial model to predict the success of entrepreneurs in Mendocino County, California. [Internet] [Masters thesis]. Humboldt State University; 2012. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/2148/1257.

Council of Science Editors:

Barnes JM. A sociospatial model to predict the success of entrepreneurs in Mendocino County, California. [Masters Thesis]. Humboldt State University; 2012. Available from: http://hdl.handle.net/2148/1257

Kwame Nkrumah University of Science and Technology

8. Mensah, George Yaw. Determination of Some Factors that Influences Loan Default Payment: Case Study: Customers from Akatakyiman Rural Bank Ltd Komenda.

Degree: 2012, Kwame Nkrumah University of Science and Technology

URL: http://dspace.knust.edu.gh:8080/jspui/handle/123456789/4091

►

Loan Default is the failure of an applicant to fulfil his/her obligation with respect to repayment of loans. Loan default lowest the financial capacity of… (more)

Subjects/Keywords: Loan default; Logistic regression; Risk

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APA (6^th Edition):

Mensah, G. Y. (2012). Determination of Some Factors that Influences Loan Default Payment: Case Study: Customers from Akatakyiman Rural Bank Ltd Komenda. (Thesis). Kwame Nkrumah University of Science and Technology. Retrieved from http://dspace.knust.edu.gh:8080/jspui/handle/123456789/4091

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mensah, George Yaw. “Determination of Some Factors that Influences Loan Default Payment: Case Study: Customers from Akatakyiman Rural Bank Ltd Komenda.” 2012. Thesis, Kwame Nkrumah University of Science and Technology. Accessed February 21, 2020. http://dspace.knust.edu.gh:8080/jspui/handle/123456789/4091.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mensah, George Yaw. “Determination of Some Factors that Influences Loan Default Payment: Case Study: Customers from Akatakyiman Rural Bank Ltd Komenda.” 2012. Web. 21 Feb 2020.

Vancouver:

Mensah GY. Determination of Some Factors that Influences Loan Default Payment: Case Study: Customers from Akatakyiman Rural Bank Ltd Komenda. [Internet] [Thesis]. Kwame Nkrumah University of Science and Technology; 2012. [cited 2020 Feb 21]. Available from: http://dspace.knust.edu.gh:8080/jspui/handle/123456789/4091.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mensah GY. Determination of Some Factors that Influences Loan Default Payment: Case Study: Customers from Akatakyiman Rural Bank Ltd Komenda. [Thesis]. Kwame Nkrumah University of Science and Technology; 2012. Available from: http://dspace.knust.edu.gh:8080/jspui/handle/123456789/4091

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Colorado School of Mines

9. Cherry, Lisa. Predicting parcel scale redevelopment within the Berkeley neighborhood in Denver, Colorado using linear and logistic regression.

Degree: MS(M.S.), Civil and Environmental Engineering, 2017, Colorado School of Mines

URL: http://hdl.handle.net/11124/170658

► Many water resource issues associated with urban development result from increased impervious cover. As impervious cover increases, rainwater infiltration decreases leading to increased flows and… (more)

▼ Many water resource issues associated with urban development result from increased impervious cover. As impervious cover increases, rainwater infiltration decreases leading to increased flows and potentially higher pollutant loads in the runoff. Most of the prior research on this topic investigates the increase of impervious cover through the transformation of undeveloped to developed regions, or the expansion of dense urban development into outlying suburban areas. A topic that is not as widely understood is the impact of infill redevelopment on stormwater runoff. Infill redevelopment is rapidly occurring in many Denver neighborhoods, where previously developed properties with low-density structures are being replaced by larger, higher density units. Regardless of impervious cover increase, these redevelopment projects are only required to incorporate stormwater detention and treatment systems if they are greater than one acre. Due to most of the redevelopment in Denver (86%) occurring on sites less than one acre, the burden of stormwater treatment and detention ultimately falls on the city. This study focuses on modeling the spatial distribution of infill re-development on a parcel scale to investigate its cumulative impacts on stormwater quality and quantity for near-term and future conditions. Future redevelopment and imperviousness is determined by distributing a “business as usual” linear growth scenario to the parcels with the greatest probability of future redevelopment. Then, a logistic regression model is used to determine the parcels that will be redeveloped. Results indicate that building cover change within study site from 2004 – 2014 followed a linear pattern. During this period the total building cover increased by 17% or 1.7 % per year on average. The logistic regression model determined the total value, year built, percent difference between current and max building cover, the current use classification: rowhomes, and current use classification apartments to be the greatest predictors of redevelopment, resulting in a model that was 81 % accurate. The "Building to Land Area Ratio" variable was found to be highly correlated with the “Improvement to Land Value Ratio”. However, the “Building to Land Area Ratio” was found to be a better predictor of redevelopment. The final model estimated an increase of 820,498 sq. ft. (18.8 acres) in building coverage between 2014 and 2024. This method will provide municipalities with a tool that can be used to estimate parcel scale impervious cover growth from publicly available planning data resulting in more informed urban watershed planning and policy development. Advisors/Committee Members: McCray, John E. (advisor), Hogue, Terri S. (committee member), Eisenstein, William (committee member).

Subjects/Keywords: Logistic regression; Redevelopment; Parcel; Infill

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cherry, L. (2017). Predicting parcel scale redevelopment within the Berkeley neighborhood in Denver, Colorado using linear and logistic regression. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170658

Chicago Manual of Style (16^th Edition):

Cherry, Lisa. “Predicting parcel scale redevelopment within the Berkeley neighborhood in Denver, Colorado using linear and logistic regression.” 2017. Masters Thesis, Colorado School of Mines. Accessed February 21, 2020. http://hdl.handle.net/11124/170658.

MLA Handbook (7^th Edition):

Cherry, Lisa. “Predicting parcel scale redevelopment within the Berkeley neighborhood in Denver, Colorado using linear and logistic regression.” 2017. Web. 21 Feb 2020.

Vancouver:

Cherry L. Predicting parcel scale redevelopment within the Berkeley neighborhood in Denver, Colorado using linear and logistic regression. [Internet] [Masters thesis]. Colorado School of Mines; 2017. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/11124/170658.

Council of Science Editors:

Cherry L. Predicting parcel scale redevelopment within the Berkeley neighborhood in Denver, Colorado using linear and logistic regression. [Masters Thesis]. Colorado School of Mines; 2017. Available from: http://hdl.handle.net/11124/170658

10. Kwémou Djoukoué, Marius. Réduction de dimension en régression logistique, application aux données actu-palu : Dimension reduction in logistic regression, application to actu-palu data.

Degree: Docteur es, Mathématiques appliquées, 2014, Evry-Val d'Essonne; Université de Saint-Louis (Sénégal)

URL: http://www.theses.fr/2014EVRY0030

►

Cette thèse est consacrée à la sélection de variables ou de modèles en régression logistique. Elle peut-être divisée en deux parties, une partie appliquée et… (more)

▼

Cette thèse est consacrée à la sélection de variables ou de modèles en régression logistique. Elle peut-être divisée en deux parties, une partie appliquée et une partie méthodologique. La partie appliquée porte sur l'analyse des données d'une grande enquête socio - épidémiologique dénommée actu-palu. Ces grandes enquêtes socio - épidémiologiques impliquent généralement un nombre considérable de variables explicatives. Le contexte est par nature dit de grande dimension. En raison du fléau de la dimension, le modèle de régression logistique n'est pas directement applicable. Nous procédons en deux étapes, une première étape de réduction du nombre de variables par les méthodes Lasso, Group Lasso et les forêts aléatoires. La deuxième étape consiste à appliquer le modèle logistique au sous-ensemble de variables sélectionné à la première étape. Ces méthodes ont permis de sélectionner les variables pertinentes pour l'identification des foyers à risque d'avoir un épisode fébrile chez un enfant de 2 à 10 ans à Dakar. La partie méthodologique, composée de deux sous-parties, porte sur l'établissement de propriétés techniques d'estimateurs dans le modèle de régression logistique non paramétrique. Ces estimateurs sont obtenus par maximum de vraisemblance pénalisé, dans un cas avec une pénalité de type Lasso ou Group Lasso et dans l'autre cas avec une pénalité de type 1 exposant 0. Dans un premier temps, nous proposons des versions pondérées des estimateurs Lasso et Group Lasso pour le modèle logistique non paramétrique. Nous établissons des inégalités oracles non asymptotiques pour ces estimateurs. Un deuxième ensemble de résultats vise à étendre le principe de sélection de modèle introduit par Birgé et Massart (2001) à la régression logistique. Cette sélection se fait via des critères du maximum de vraisemblance pénalisé. Nous proposons dans ce contexte des critères de sélection de modèle, et nous établissons des inégalités oracles non asymptotiques pour les estimateurs sélectionnés. La pénalité utilisée, dépendant uniquement des données, est calibrée suivant l'idée de l'heuristique de pente. Tous les résultats de la partie méthodologique sont illustrés par des études de simulations numériques.

This thesis is devoted to variables selection or model selection in logistic regression. The applied part focuses on the analysis of data from a large socioepidémiological survey, called actu-palu. These large socioepidemiological survey typically involve a considerable number of explanatory variables. This is well-known as high-dimensional setting. Due to the curse of dimensionality, logistic regression model is no longer reliable. We proceed in two steps, a first step of reducing the number of variables by the Lasso, Group Lasso ans random forests methods. The second step is to apply the logistic model to the sub-set of variables selected in the first step. These methods have helped to select relevant variables for the identification of households at risk of having febrile episode amongst children from 2 to 10 years old in Dakar. In…

Advisors/Committee Members: Taupin, Marie-Luce (thesis director), Diongue, Abdou Kâ (thesis director).

Subjects/Keywords: Régression logistique; Logistic regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kwémou Djoukoué, M. (2014). Réduction de dimension en régression logistique, application aux données actu-palu : Dimension reduction in logistic regression, application to actu-palu data. (Doctoral Dissertation). Evry-Val d'Essonne; Université de Saint-Louis (Sénégal). Retrieved from http://www.theses.fr/2014EVRY0030

Chicago Manual of Style (16^th Edition):

Kwémou Djoukoué, Marius. “Réduction de dimension en régression logistique, application aux données actu-palu : Dimension reduction in logistic regression, application to actu-palu data.” 2014. Doctoral Dissertation, Evry-Val d'Essonne; Université de Saint-Louis (Sénégal). Accessed February 21, 2020. http://www.theses.fr/2014EVRY0030.

MLA Handbook (7^th Edition):

Kwémou Djoukoué, Marius. “Réduction de dimension en régression logistique, application aux données actu-palu : Dimension reduction in logistic regression, application to actu-palu data.” 2014. Web. 21 Feb 2020.

Vancouver:

Kwémou Djoukoué M. Réduction de dimension en régression logistique, application aux données actu-palu : Dimension reduction in logistic regression, application to actu-palu data. [Internet] [Doctoral dissertation]. Evry-Val d'Essonne; Université de Saint-Louis (Sénégal); 2014. [cited 2020 Feb 21]. Available from: http://www.theses.fr/2014EVRY0030.

Council of Science Editors:

Kwémou Djoukoué M. Réduction de dimension en régression logistique, application aux données actu-palu : Dimension reduction in logistic regression, application to actu-palu data. [Doctoral Dissertation]. Evry-Val d'Essonne; Université de Saint-Louis (Sénégal); 2014. Available from: http://www.theses.fr/2014EVRY0030

University of Manitoba

11. Shen, Yi (Jack). A multinomial logistic regression analysis of youth gambling in Manitoba using Cycle 2 of the Manitoba Longitudinal Study of Young Adults.

Degree: Sociology, 2018, University of Manitoba

URL: http://hdl.handle.net/1993/32795

► Problem gambling is still a relatively new form of addiction in terms of the amount of research that has been put into it. The data… (more)

Subjects/Keywords: Problem gambling; Logistic regression

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APA (6^th Edition):

Shen, Y. (. (2018). A multinomial logistic regression analysis of youth gambling in Manitoba using Cycle 2 of the Manitoba Longitudinal Study of Young Adults. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/32795

Chicago Manual of Style (16^th Edition):

Shen, Yi (Jack). “A multinomial logistic regression analysis of youth gambling in Manitoba using Cycle 2 of the Manitoba Longitudinal Study of Young Adults.” 2018. Masters Thesis, University of Manitoba. Accessed February 21, 2020. http://hdl.handle.net/1993/32795.

MLA Handbook (7^th Edition):

Shen, Yi (Jack). “A multinomial logistic regression analysis of youth gambling in Manitoba using Cycle 2 of the Manitoba Longitudinal Study of Young Adults.” 2018. Web. 21 Feb 2020.

Vancouver:

Shen Y(. A multinomial logistic regression analysis of youth gambling in Manitoba using Cycle 2 of the Manitoba Longitudinal Study of Young Adults. [Internet] [Masters thesis]. University of Manitoba; 2018. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1993/32795.

Council of Science Editors:

Shen Y(. A multinomial logistic regression analysis of youth gambling in Manitoba using Cycle 2 of the Manitoba Longitudinal Study of Young Adults. [Masters Thesis]. University of Manitoba; 2018. Available from: http://hdl.handle.net/1993/32795

12. Ishikawa, Noemi Ichihara. Uso de transformações em modelos de regressão logística.

Degree: Mestrado, Estatística, 2007, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/45/45133/tde-05062007-202656/ ;

►

Modelos para dados binários são bastante utilizados em várias situações práticas. Transformações em Análise de Regressão podem ser aplicadas para linearizar ou simplificar o modelo… (more)

Subjects/Keywords: regression logistic regression models; transformações regressão logística

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APA (6^th Edition):

Ishikawa, N. I. (2007). Uso de transformações em modelos de regressão logística. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/45/45133/tde-05062007-202656/ ;

Chicago Manual of Style (16^th Edition):

Ishikawa, Noemi Ichihara. “Uso de transformações em modelos de regressão logística.” 2007. Masters Thesis, University of São Paulo. Accessed February 21, 2020. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-05062007-202656/ ;.

MLA Handbook (7^th Edition):

Ishikawa, Noemi Ichihara. “Uso de transformações em modelos de regressão logística.” 2007. Web. 21 Feb 2020.

Vancouver:

Ishikawa NI. Uso de transformações em modelos de regressão logística. [Internet] [Masters thesis]. University of São Paulo; 2007. [cited 2020 Feb 21]. Available from: http://www.teses.usp.br/teses/disponiveis/45/45133/tde-05062007-202656/ ;.

Council of Science Editors:

Ishikawa NI. Uso de transformações em modelos de regressão logística. [Masters Thesis]. University of São Paulo; 2007. Available from: http://www.teses.usp.br/teses/disponiveis/45/45133/tde-05062007-202656/ ;

University of North Texas

13. Weng, Yu. Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models.

Degree: 2013, University of North Texas

URL: https://digital.library.unt.edu/ark:/67531/metadc407796/

► We consider the problem of maximum likelihood estimation of logistic sinusoidal regression models and develop some asymptotic theory including the consistency and joint rates of… (more)

Subjects/Keywords: Maximum likelihood; estimation; logistic regression; sinusoidal regression

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APA (6^th Edition):

Weng, Y. (2013). Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc407796/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Weng, Yu. “Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models.” 2013. Thesis, University of North Texas. Accessed February 21, 2020. https://digital.library.unt.edu/ark:/67531/metadc407796/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Weng, Yu. “Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models.” 2013. Web. 21 Feb 2020.

Vancouver:

Weng Y. Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models. [Internet] [Thesis]. University of North Texas; 2013. [cited 2020 Feb 21]. Available from: https://digital.library.unt.edu/ark:/67531/metadc407796/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Weng Y. Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models. [Thesis]. University of North Texas; 2013. Available from: https://digital.library.unt.edu/ark:/67531/metadc407796/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Florida International University

14. Huang, Lixin. Predicting Hurricane Evacuation Decisions: When, How Many, and How Far.

Degree: Civil Engineering, 2011, Florida International University

URL: https://digitalcommons.fiu.edu/etd/461 ; 10.25148/etd.FI11081005 ; FI11081005

► Traffic from major hurricane evacuations is known to cause severe gridlocks on evacuation routes. Better prediction of the expected amount of evacuation traffic is… (more)

▼ Traffic from major hurricane evacuations is known to cause severe gridlocks on evacuation routes. Better prediction of the expected amount of evacuation traffic is needed to improve the decision-making process for the required evacuation routes and possible deployment of special traffic operations, such as contraflow. The objective of this dissertation is to develop prediction models to predict the number of daily trips and the evacuation distance during a hurricane evacuation. Two data sets from the surveys of the evacuees from Hurricanes Katrina and Ivan were used in the models' development. The data sets included detailed information on the evacuees, including their evacuation days, evacuation distance, distance to the hurricane location, and their associated socioeconomic characteristics, including gender, age, race, household size, rental status, income, and education level. Three prediction models were developed. The evacuation trip and rate models were developed using logistic regression. Together, they were used to predict the number of daily trips generated before hurricane landfall. These daily predictions allowed for more detailed planning over the traditional models, which predicted the total number of trips generated from an entire evacuation. A third model developed attempted to predict the evacuation distance using Geographically Weighted Regression (GWR), which was able to account for the spatial variations found among the different evacuation areas, in terms of impacts from the model predictors. All three models were developed using the survey data set from Hurricane Katrina and then evaluated using the survey data set from Hurricane Ivan. All of the models developed provided logical results. The logistic models showed that larger households with people under age six were more likely to evacuate than smaller households. The GWR-based evacuation distance model showed that the household with children under age six, income, and proximity of household to hurricane path, all had an impact on the evacuation distances. While the models were found to provide logical results, it was recognized that they were calibrated and evaluated with relatively limited survey data. The models can be refined with additional data from future hurricane surveys, including additional variables, such as the time of day of the evacuation. Advisors/Committee Members: Albert Gan, L. David Shen, Mohammed Hadi, Zhenmin Chen.

Subjects/Keywords: Hurricane Evacuation; Logistic Regression; Geographically Weighted Regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Huang, L. (2011). Predicting Hurricane Evacuation Decisions: When, How Many, and How Far. (Thesis). Florida International University. Retrieved from https://digitalcommons.fiu.edu/etd/461 ; 10.25148/etd.FI11081005 ; FI11081005

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Huang, Lixin. “Predicting Hurricane Evacuation Decisions: When, How Many, and How Far.” 2011. Thesis, Florida International University. Accessed February 21, 2020. https://digitalcommons.fiu.edu/etd/461 ; 10.25148/etd.FI11081005 ; FI11081005.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Huang, Lixin. “Predicting Hurricane Evacuation Decisions: When, How Many, and How Far.” 2011. Web. 21 Feb 2020.

Vancouver:

Huang L. Predicting Hurricane Evacuation Decisions: When, How Many, and How Far. [Internet] [Thesis]. Florida International University; 2011. [cited 2020 Feb 21]. Available from: https://digitalcommons.fiu.edu/etd/461 ; 10.25148/etd.FI11081005 ; FI11081005.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Huang L. Predicting Hurricane Evacuation Decisions: When, How Many, and How Far. [Thesis]. Florida International University; 2011. Available from: https://digitalcommons.fiu.edu/etd/461 ; 10.25148/etd.FI11081005 ; FI11081005

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of South Africa

15. Muchabaiwa, Honest. Logistic regression to determine significant factors associated with share price change .

Degree: 2013, University of South Africa

URL: http://hdl.handle.net/10500/13229

► This thesis investigates the factors that are associated with annual changes in the share price of Johannesburg Stock Exchange (JSE) listed companies. In this study,… (more)

Subjects/Keywords: Logistic regression; Binary logistic regression; Share price; Stock exchange; Akaike’s Information Criterion; Wald Test; Score test; Enter method; Stepwise logistic regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Muchabaiwa, H. (2013). Logistic regression to determine significant factors associated with share price change . (Masters Thesis). University of South Africa. Retrieved from http://hdl.handle.net/10500/13229

Chicago Manual of Style (16^th Edition):

Muchabaiwa, Honest. “Logistic regression to determine significant factors associated with share price change .” 2013. Masters Thesis, University of South Africa. Accessed February 21, 2020. http://hdl.handle.net/10500/13229.

MLA Handbook (7^th Edition):

Muchabaiwa, Honest. “Logistic regression to determine significant factors associated with share price change .” 2013. Web. 21 Feb 2020.

Vancouver:

Muchabaiwa H. Logistic regression to determine significant factors associated with share price change . [Internet] [Masters thesis]. University of South Africa; 2013. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10500/13229.

Council of Science Editors:

Muchabaiwa H. Logistic regression to determine significant factors associated with share price change . [Masters Thesis]. University of South Africa; 2013. Available from: http://hdl.handle.net/10500/13229

Texas A&M University

16. Miao, Jingang. New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics.

Degree: 2014, Texas A&M University

URL: http://hdl.handle.net/1969.1/153244

► As a probabilistic statistical classification model, logistic regression (or logit regression) is widely used to model the outcome of a categorical dependent variable based on… (more)

▼ As a probabilistic statistical classification model, logistic regression (or logit regression) is widely used to model the outcome of a categorical dependent variable based on one or more predictor variables/features. We study two problems related to logistic regression with applications in biostatistics. In the first problem, we study multivariate disease classification in the presence of partially missing disease traits. In modern cancer epidemiology, diseases are classified based on pathologic and molecular traits, and different combinations of these traits give rise to many disease subtypes. The effect of predictor variables can be measured by fitting a polytomous logistic model to such data. The differences (heterogeneity) among the relative risk parameters associated with subtypes are of great interest to better understand disease etiology. Due to the heterogeneity of the relative risk parameters, when a risk factor is changed, the prevalence of one subtype may change more than that of another subtype does. Estimation of the heterogeneity parameters is difficult when disease trait information is only partially observed and the number of disease subtypes is large. We consider a robust semiparametric approach based on the pseudo conditional likelihood for estimating these heterogeneity parameters. Through simulation studies, we compare the robustness and efficiency of our approach with the maximum likelihood approach. The method is then applied to analyze data from the American Cancer Society Cancer Prevention Study (CPS) II Nutrition Cohort. Weight gain was associated with the risk of breast cancer and the association varies by disease subtype. In the second problem, we use a semiparametric Bayesian method to handle measurement errors. In nutritional epidemiological studies, nutrient intakes are often measured via food frequency questionnaires and 24-hour dietary recalls. Due to self reporting, recall error, and other reasons, the measured nutrient intakes can involve a substantial amount of noise. While independence assumption between the measurement error and the true predictor is likely to be a reasonable assumption for the main effect of the predictors, this assumption is not tenable for the interaction effect of two predictors measured with error. Although there are a number of flexible methods for handling additive, homogeneous measurement error in predictors in logistic regression models, relatively less attention has been paid to handling measurement error that depends on the unobserved predictor. Therefore, we propose a semiparametric Bayesian method for handling this unorthodox measurement error scenario in logistic regression models in the presence of the interaction term. The proposed method is also designed to handle partially missing values for the error-prone surrogate variables. Through simulation studies, we assess some operating characteristics of the proposed method and compare it with the simulation extrapolation and the regression calibration method. Our method has smaller biases than the… Advisors/Committee Members: Wang, Suojin (advisor), Sinha, Samiran (advisor), Longnecker, Michael (committee member), McKyer, E. Lisako J (committee member).

Subjects/Keywords: Logistic regression; Measurement error; Disease classification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Miao, J. (2014). New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153244

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Miao, Jingang. “New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics.” 2014. Thesis, Texas A&M University. Accessed February 21, 2020. http://hdl.handle.net/1969.1/153244.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Miao, Jingang. “New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics.” 2014. Web. 21 Feb 2020.

Vancouver:

Miao J. New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/1969.1/153244.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Miao J. New Advances in Logistic Regression for Handling Missing and Mismeasured Data with Applications in Biostatistics. [Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153244

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Baylor University

17. [No author]. Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression.

Degree: 2015, Baylor University

URL: http://hdl.handle.net/2104/9557

► Conventional Phase II clinical trial designs usually employ a logistic regression model to analyze the efficacy of a new drug and, therefore, assumes monotone dose-response… (more)

▼ Conventional Phase II clinical trial designs usually employ a logistic regression model to analyze the efficacy of a new drug and, therefore, assumes monotone dose-response relationship. Also, the logistic regression model requires the response to be categorical and, thus, it is not applicable for continuous data. The traditional design in Phase II determines if a new drug will be further tested in Phase III based on only drug efficacy and allocates an equal number of patients to each dosage, ignoring dose efficacy. Because of the limitations of conventional clinical trial designs, new adaptive designs have been proposed by researchers to improve the flexibility and adaptability of conventional designs. In Chapter Two we propose an adaptive Bayesian design that uses a bivariate normal dynamic linear model for a Phase II clinical trial, and we compare its performance to a Bayesian fixed or non-adaptive design. The proposed Bayesian adaptive design can be utilized for continuous data and can model various dose-response relationships. We remark that for many dose-response relationships, our proposed adaptive Bayesian design can use fewer patients to obtain a correct decision concerning a drug's efficacy than the Bayesian fixed design. Missing data arises in almost all research; that is, part of the data are missing for a subject. A data analyst must decide how to cope with the missing data from among the numerous imputation methods that can be used. However, one might not know which imputation method is the best. The objective of this study is to evaluate the efficacy of five imputation methods. In Chapter Four, we have compared the performance of complete-data-only, single-mean imputation, conditional-mean imputation, multiple imputation by chained equations and hotdeck imputation methods for prediction of a logistic regression model, for the missing-completely-at-random and missing-at-random mechanisms. These five imputation methods yield different results for small sample sizes, and the difference decreases with an increasing sample size. Surprisingly, a single-mean imputation method performs as well as the multiple imputation methods compared here. Advisors/Committee Members: Young, Dean M (advisor).

Subjects/Keywords: Clinical trial. Dynamic linear model. Logistic regression.

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APA (6^th Edition):

author], [. (2015). Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. (Thesis). Baylor University. Retrieved from http://hdl.handle.net/2104/9557

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

author], [No. “Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. ” 2015. Thesis, Baylor University. Accessed February 21, 2020. http://hdl.handle.net/2104/9557.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

author], [No. “Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. ” 2015. Web. 21 Feb 2020.

Vancouver:

author] [. Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. [Internet] [Thesis]. Baylor University; 2015. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/2104/9557.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. [Thesis]. Baylor University; 2015. Available from: http://hdl.handle.net/2104/9557

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Duquesne University

18. McKibben, Michael. Predicting Bankruptcy and Catastrophic Loss: A Portfolio Approach.

Degree: MS, Computational Mathematics, 2017, Duquesne University

URL: https://dsc.duq.edu/etd/140

► This paper uses logistic regression to assign risk of catastrophic loss (defined as a loss of 80% or more of market cap value) to… (more)

Subjects/Keywords: Bankruptcy; catastrophic; cusp; logistic; Portfolio; regression

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APA (6^th Edition):

McKibben, M. (2017). Predicting Bankruptcy and Catastrophic Loss: A Portfolio Approach. (Masters Thesis). Duquesne University. Retrieved from https://dsc.duq.edu/etd/140

Chicago Manual of Style (16^th Edition):

McKibben, Michael. “Predicting Bankruptcy and Catastrophic Loss: A Portfolio Approach.” 2017. Masters Thesis, Duquesne University. Accessed February 21, 2020. https://dsc.duq.edu/etd/140.

MLA Handbook (7^th Edition):

McKibben, Michael. “Predicting Bankruptcy and Catastrophic Loss: A Portfolio Approach.” 2017. Web. 21 Feb 2020.

Vancouver:

McKibben M. Predicting Bankruptcy and Catastrophic Loss: A Portfolio Approach. [Internet] [Masters thesis]. Duquesne University; 2017. [cited 2020 Feb 21]. Available from: https://dsc.duq.edu/etd/140.

Council of Science Editors:

McKibben M. Predicting Bankruptcy and Catastrophic Loss: A Portfolio Approach. [Masters Thesis]. Duquesne University; 2017. Available from: https://dsc.duq.edu/etd/140

Duquesne University

19. Vescovi, Darren. Best Practices in Authorship Attribution of English Essays.

Degree: MS, Computational Mathematics, 2011, Duquesne University

URL: https://dsc.duq.edu/etd/1310

► Logistic regression analysis is used to determine the best practices in authorship attribution for English essays, specifically examining the methods available in JGAAP version 4.3… (more)

Subjects/Keywords: Authorship attribution; English essays; Logistic regression

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APA (6^th Edition):

Vescovi, D. (2011). Best Practices in Authorship Attribution of English Essays. (Masters Thesis). Duquesne University. Retrieved from https://dsc.duq.edu/etd/1310

Chicago Manual of Style (16^th Edition):

Vescovi, Darren. “Best Practices in Authorship Attribution of English Essays.” 2011. Masters Thesis, Duquesne University. Accessed February 21, 2020. https://dsc.duq.edu/etd/1310.

MLA Handbook (7^th Edition):

Vescovi, Darren. “Best Practices in Authorship Attribution of English Essays.” 2011. Web. 21 Feb 2020.

Vancouver:

Vescovi D. Best Practices in Authorship Attribution of English Essays. [Internet] [Masters thesis]. Duquesne University; 2011. [cited 2020 Feb 21]. Available from: https://dsc.duq.edu/etd/1310.

Council of Science Editors:

Vescovi D. Best Practices in Authorship Attribution of English Essays. [Masters Thesis]. Duquesne University; 2011. Available from: https://dsc.duq.edu/etd/1310

University of Nairobi

20. Adede, Chrisgone O. Model for predicting the probability of event occurrence using logistic regression: case for a Kenyan commercial bank .

Degree: 2012, University of Nairobi

URL: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10144

► Credit Scoring has been a key undertaking of lenders over the last few decades. However, the most common use of credit scoring has been as… (more)

Subjects/Keywords: probability; logistic regression; Kenyan commercial bank

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APA (6^th Edition):

Adede, C. O. (2012). Model for predicting the probability of event occurrence using logistic regression: case for a Kenyan commercial bank . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10144

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Adede, Chrisgone O. “Model for predicting the probability of event occurrence using logistic regression: case for a Kenyan commercial bank .” 2012. Thesis, University of Nairobi. Accessed February 21, 2020. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10144.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Adede, Chrisgone O. “Model for predicting the probability of event occurrence using logistic regression: case for a Kenyan commercial bank .” 2012. Web. 21 Feb 2020.

Vancouver:

Adede CO. Model for predicting the probability of event occurrence using logistic regression: case for a Kenyan commercial bank . [Internet] [Thesis]. University of Nairobi; 2012. [cited 2020 Feb 21]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10144.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Adede CO. Model for predicting the probability of event occurrence using logistic regression: case for a Kenyan commercial bank . [Thesis]. University of Nairobi; 2012. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10144

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Nairobi

21. Nzioki, Nicholas M. Use Of Logistic Regression Model To Determine The Key Contaminants Of Water In Yatta District .

Degree: 2012, University of Nairobi

URL: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/11957

► Over one sixth of the world's population lacks safe drinking-water sources. The water crisis in Kenya is due not only to the wave of droughts… (more)

Subjects/Keywords: Logistic regression; Contaminants of water; Yatta District

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APA (6^th Edition):

Nzioki, N. M. (2012). Use Of Logistic Regression Model To Determine The Key Contaminants Of Water In Yatta District . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/11957

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nzioki, Nicholas M. “Use Of Logistic Regression Model To Determine The Key Contaminants Of Water In Yatta District .” 2012. Thesis, University of Nairobi. Accessed February 21, 2020. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/11957.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nzioki, Nicholas M. “Use Of Logistic Regression Model To Determine The Key Contaminants Of Water In Yatta District .” 2012. Web. 21 Feb 2020.

Vancouver:

Nzioki NM. Use Of Logistic Regression Model To Determine The Key Contaminants Of Water In Yatta District . [Internet] [Thesis]. University of Nairobi; 2012. [cited 2020 Feb 21]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/11957.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nzioki NM. Use Of Logistic Regression Model To Determine The Key Contaminants Of Water In Yatta District . [Thesis]. University of Nairobi; 2012. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/11957

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Nairobi

22. Obayo, Eunice. Evaluation of vct utilization by women in Kenya using the logistic regression model .

Degree: 2010, University of Nairobi

URL: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14223

► HIV/AIDS pandemic is a global crisis with consequences that will be felt for decades to come. It has already claimed more than 25 million lives… (more)

Subjects/Keywords: Evaluation; Vct utilization; Women; Logistic regression model

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APA (6^th Edition):

Obayo, E. (2010). Evaluation of vct utilization by women in Kenya using the logistic regression model . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14223

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Obayo, Eunice. “Evaluation of vct utilization by women in Kenya using the logistic regression model .” 2010. Thesis, University of Nairobi. Accessed February 21, 2020. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14223.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Obayo, Eunice. “Evaluation of vct utilization by women in Kenya using the logistic regression model .” 2010. Web. 21 Feb 2020.

Vancouver:

Obayo E. Evaluation of vct utilization by women in Kenya using the logistic regression model . [Internet] [Thesis]. University of Nairobi; 2010. [cited 2020 Feb 21]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14223.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Obayo E. Evaluation of vct utilization by women in Kenya using the logistic regression model . [Thesis]. University of Nairobi; 2010. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14223

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

23. Shieh, Feng-Cheng. Using CRM Data for Customer Loyalty Prediction â A Case Study in Electrical & Electronic Industry.

Degree: Master, Information Management, 2014, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0105114-121324

► Due to the advances in information and internet technology, customers nowadays can easily acquire information about prices and specifications of desired products. Thus, how to… (more)

Subjects/Keywords: Customer Relationship Management; Logistic Regression; Brand; Loyalty

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APA (6^th Edition):

Shieh, F. (2014). Using CRM Data for Customer Loyalty Prediction â A Case Study in Electrical & Electronic Industry. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0105114-121324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shieh, Feng-Cheng. “Using CRM Data for Customer Loyalty Prediction â A Case Study in Electrical & Electronic Industry.” 2014. Thesis, NSYSU. Accessed February 21, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0105114-121324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shieh, Feng-Cheng. “Using CRM Data for Customer Loyalty Prediction â A Case Study in Electrical & Electronic Industry.” 2014. Web. 21 Feb 2020.

Vancouver:

Shieh F. Using CRM Data for Customer Loyalty Prediction â A Case Study in Electrical & Electronic Industry. [Internet] [Thesis]. NSYSU; 2014. [cited 2020 Feb 21]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0105114-121324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shieh F. Using CRM Data for Customer Loyalty Prediction â A Case Study in Electrical & Electronic Industry. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0105114-121324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

24. Lin, Shui-Pa. An Empirical Analysis of The Effect of Cram Education on Civil Servantâs Human Capital.

Degree: Master, EMPP, 2014, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0611114-211030

► âCram schoolâ, a common phenomenon in Taiwan, steady became a kind of trend now. Numbers of cram schools grew up dramatically in the past decade.… (more)

Subjects/Keywords: Logistic Regression; Cram school; Officersâ Test

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APA (6^th Edition):

Lin, S. (2014). An Empirical Analysis of The Effect of Cram Education on Civil Servantâs Human Capital. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0611114-211030

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lin, Shui-Pa. “An Empirical Analysis of The Effect of Cram Education on Civil Servantâs Human Capital.” 2014. Thesis, NSYSU. Accessed February 21, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0611114-211030.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lin, Shui-Pa. “An Empirical Analysis of The Effect of Cram Education on Civil Servantâs Human Capital.” 2014. Web. 21 Feb 2020.

Vancouver:

Lin S. An Empirical Analysis of The Effect of Cram Education on Civil Servantâs Human Capital. [Internet] [Thesis]. NSYSU; 2014. [cited 2020 Feb 21]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0611114-211030.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin S. An Empirical Analysis of The Effect of Cram Education on Civil Servantâs Human Capital. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0611114-211030

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

25. Chao, Tung-bo. Analysis of Unexpected Readmission of Elderly Pneumonia Patient.

Degree: Master, Institute of Health Care Management, 2012, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0626112-185914

► Objectives: This Study wanted to analysis the characteristics of the elder adult who had hospitalized with pneumonia. We also evaluated the factors that will affect… (more)

▼ Objectives: This Study wanted to analysis the characteristics of the elder adult who had hospitalized with pneumonia. We also evaluated the factors that will affect the unexpected readmission in elderly pneumonia patients. Methods: This is a retrospective cohort study design. The study data was collected 341 pneumonia patients who have hospitalized in a general teaching hospital in Kaohsiung city from year 2009 to 2010. The study population was divided into two groups, the sample size of the old group (age >= 65yrs), and the young group (age < 65yrs) was 173 and 168, respectively. The methods of stepwise multiple logistic regressions were needed to evaluate the association between aging and different days of unplanned readmission in adult pneumonia patients. Results: All the 341 adult pneumonia patients, we found 613 male and 926 female. The demography characteristic of the study subjects, the means of age was 61.9yrs (s.d. = 19.3yrs), and BMI was 23.4 kg/m2 (s.d. = 4.5 kg/m2). The percentage of ICD-9-CM that code 486 was 95.6%. Most patients were community-acquired pneumonia (98.8%), hospitalized from emergency room (85.3%), and admission in general wards (92.7%). The unplanned readmission within 14/30 days, 60 days, and 90days were 9.1%, 11.7%, and 15.0%, respectively. The significant factors that were associated with readmission within 14 days include age, Hb, hospitalized days, hypertension, and other disease. When we used the multiple logistic regression analysis to adjust the other variables, only age still significant with readmission within 14 days (the crude OR of the old group was 4.561, adjusted OR was 2.714, 95% CI of OR from 1.002 to 7.353). In the stepwise multiple logistic regression models, the variable that was associated with readmission with 14 or 30 days were age (>= 65yrs, OR = 3.025), WBC (>=10750 mm3, OR=2.917), and Hb (>=12.4 g/dL, OR=0.390). We remain the elderly subjects to evaluate the factor that will influence readmission states. In all the stepwise logistic regression models, we found the experience with used endotracheal tube in the hospitalized period were the significant increases the readmission rate within 14 or 30 days, 60 days, and 90 days. Conclusion: In our study shows that the situations of unexpected readmission in pneumonia patients were strong association with aging. We suggest that the indicator of medical quality should be adjusted before we comparison the readmission rate in the different institute. The major factors that will be associated to affect the readmission states were endotracheal tube used (significant with 14 or 30 days readmission rate), CRP level (significant with 60 days and 90 days readmission rate), and Hb level (significant with 60 days and 90 days readmission rate). Advisors/Committee Members: Chen-guo Ker (chair), Ying-chun Li (committee member), Yuan-yi Chia (chair).

Subjects/Keywords: unexpected readmission; pneumonia; logistic regression analysis; elderly

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chao, T. (2012). Analysis of Unexpected Readmission of Elderly Pneumonia Patient. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0626112-185914

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chao, Tung-bo. “Analysis of Unexpected Readmission of Elderly Pneumonia Patient.” 2012. Thesis, NSYSU. Accessed February 21, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0626112-185914.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chao, Tung-bo. “Analysis of Unexpected Readmission of Elderly Pneumonia Patient.” 2012. Web. 21 Feb 2020.

Vancouver:

Chao T. Analysis of Unexpected Readmission of Elderly Pneumonia Patient. [Internet] [Thesis]. NSYSU; 2012. [cited 2020 Feb 21]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0626112-185914.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chao T. Analysis of Unexpected Readmission of Elderly Pneumonia Patient. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0626112-185914

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Bowling Green State University

26. Rashid, Mamunur. Inference on Logistic Regression Models.

Degree: PhD, Mathematics/Probability and Statistics, 2008, Bowling Green State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1214165101

► The logistic regression model is one of the popular mathematical models for the analysis of binary data with applications in physical, biomedical, and behavioral… (more)

Subjects/Keywords: Statistics; LOGISTIC REGRESSION MODELS; z1; bootstrap

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Rashid, M. (2008). Inference on Logistic Regression Models. (Doctoral Dissertation). Bowling Green State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1214165101

Chicago Manual of Style (16^th Edition):

Rashid, Mamunur. “Inference on Logistic Regression Models.” 2008. Doctoral Dissertation, Bowling Green State University. Accessed February 21, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1214165101.

MLA Handbook (7^th Edition):

Rashid, Mamunur. “Inference on Logistic Regression Models.” 2008. Web. 21 Feb 2020.

Vancouver:

Rashid M. Inference on Logistic Regression Models. [Internet] [Doctoral dissertation]. Bowling Green State University; 2008. [cited 2020 Feb 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1214165101.

Council of Science Editors:

Rashid M. Inference on Logistic Regression Models. [Doctoral Dissertation]. Bowling Green State University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1214165101

University of Otago

27. Buchanan, Robert. Numerical methods for bankruptcy prediction: A comparison between data envelopment analysis and logistic regression .

Degree: 2011, University of Otago

URL: http://hdl.handle.net/10523/1373

► This research examines the efficacy of Data Envelopment Analysis (DEA) as a model for bankruptcy prediction compared to the logistic regression method. A sample of… (more)

Subjects/Keywords: Data Envelopment Analysis; bankruptcy prediction; logistic regression

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APA (6^th Edition):

Buchanan, R. (2011). Numerical methods for bankruptcy prediction: A comparison between data envelopment analysis and logistic regression . (Masters Thesis). University of Otago. Retrieved from http://hdl.handle.net/10523/1373

Chicago Manual of Style (16^th Edition):

Buchanan, Robert. “Numerical methods for bankruptcy prediction: A comparison between data envelopment analysis and logistic regression .” 2011. Masters Thesis, University of Otago. Accessed February 21, 2020. http://hdl.handle.net/10523/1373.

MLA Handbook (7^th Edition):

Buchanan, Robert. “Numerical methods for bankruptcy prediction: A comparison between data envelopment analysis and logistic regression .” 2011. Web. 21 Feb 2020.

Vancouver:

Buchanan R. Numerical methods for bankruptcy prediction: A comparison between data envelopment analysis and logistic regression . [Internet] [Masters thesis]. University of Otago; 2011. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10523/1373.

Council of Science Editors:

Buchanan R. Numerical methods for bankruptcy prediction: A comparison between data envelopment analysis and logistic regression . [Masters Thesis]. University of Otago; 2011. Available from: http://hdl.handle.net/10523/1373

28. Pavlik, Kaylin. A Model to Predict Matriculation of Concordia College Applicants.

Degree: MS, Statistics, 2017, North Dakota State University

URL: http://hdl.handle.net/10365/28463

► Colleges and universities are under mounting pressure to meet enrollment goals in the face of declining college attendance. Insight into student-level probability of enrollment, as… (more)

Subjects/Keywords: College choice; Logistic regression analysis; School enrollment

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APA (6^th Edition):

Pavlik, K. (2017). A Model to Predict Matriculation of Concordia College Applicants. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/28463

Chicago Manual of Style (16^th Edition):

Pavlik, Kaylin. “A Model to Predict Matriculation of Concordia College Applicants.” 2017. Masters Thesis, North Dakota State University. Accessed February 21, 2020. http://hdl.handle.net/10365/28463.

MLA Handbook (7^th Edition):

Pavlik, Kaylin. “A Model to Predict Matriculation of Concordia College Applicants.” 2017. Web. 21 Feb 2020.

Vancouver:

Pavlik K. A Model to Predict Matriculation of Concordia College Applicants. [Internet] [Masters thesis]. North Dakota State University; 2017. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10365/28463.

Council of Science Editors:

Pavlik K. A Model to Predict Matriculation of Concordia College Applicants. [Masters Thesis]. North Dakota State University; 2017. Available from: http://hdl.handle.net/10365/28463

Virginia Tech

29. VanDerwerker, Tiffany Jebson. Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model.

Degree: MS, Geosciences, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/77957

► For this study, I have constructed a logistic regression model, using existing datasets of environmental parameters to predict the probability of As concentrations above 5… (more)

Subjects/Keywords: Arsenic; Groundwater; Aquifer Vulnerability; Logistic Regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

VanDerwerker, T. J. (2016). Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77957

Chicago Manual of Style (16^th Edition):

VanDerwerker, Tiffany Jebson. “Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model.” 2016. Masters Thesis, Virginia Tech. Accessed February 21, 2020. http://hdl.handle.net/10919/77957.

MLA Handbook (7^th Edition):

VanDerwerker, Tiffany Jebson. “Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model.” 2016. Web. 21 Feb 2020.

Vancouver:

VanDerwerker TJ. Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10919/77957.

Council of Science Editors:

VanDerwerker TJ. Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/77957

University of St. Andrews

30. Lim, Ji-Hyun. A computational approach to discovering p53 binding sites in the human genome .

Degree: 2013, University of St. Andrews

URL: http://hdl.handle.net/10023/3388

► The tumour suppressor p53 protein plays a central role in the DNA damage response/checkpoint pathways leading to DNA repair, cell cycle arrest, apoptosis and senescence.… (more)

Subjects/Keywords: p53; Regulatory regions; Bioinformatics; Logistic regression; Epigenetics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lim, J. (2013). A computational approach to discovering p53 binding sites in the human genome . (Thesis). University of St. Andrews. Retrieved from http://hdl.handle.net/10023/3388

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lim, Ji-Hyun. “A computational approach to discovering p53 binding sites in the human genome .” 2013. Thesis, University of St. Andrews. Accessed February 21, 2020. http://hdl.handle.net/10023/3388.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lim, Ji-Hyun. “A computational approach to discovering p53 binding sites in the human genome .” 2013. Web. 21 Feb 2020.

Vancouver:

Lim J. A computational approach to discovering p53 binding sites in the human genome . [Internet] [Thesis]. University of St. Andrews; 2013. [cited 2020 Feb 21]. Available from: http://hdl.handle.net/10023/3388.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lim J. A computational approach to discovering p53 binding sites in the human genome . [Thesis]. University of St. Andrews; 2013. Available from: http://hdl.handle.net/10023/3388

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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Open Access Theses and Dissertations