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You searched for +publisher:"University of Kansas" +contributor:("Deboeck, Pascal R."). Showing records 1 – 20 of 20 total matches.

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University of Kansas

1. McCune, Luke A. A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling.

Degree: MA, Psychology, 2014, University of Kansas

 Longitudinal planned missing, represented in the literature by the time-lag model (McArdle&Woodcock, 1997) and the cohort sequential design (Nesselroade&Baltes, 1979), has been thus far restricted… (more)

Subjects/Keywords: Quantitative psychology and psychometrics; Statistics; accelerated longitudinal; cohort sequential; longitudinal; planned missing; simulation

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APA (6th Edition):

McCune, L. A. (2014). A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling. (Masters Thesis). University of Kansas. Retrieved from http://hdl.handle.net/1808/16867

Chicago Manual of Style (16th Edition):

McCune, Luke A. “A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling.” 2014. Masters Thesis, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/16867.

MLA Handbook (7th Edition):

McCune, Luke A. “A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling.” 2014. Web. 20 Sep 2019.

Vancouver:

McCune LA. A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling. [Internet] [Masters thesis]. University of Kansas; 2014. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/16867.

Council of Science Editors:

McCune LA. A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling. [Masters Thesis]. University of Kansas; 2014. Available from: http://hdl.handle.net/1808/16867


University of Kansas

2. Shaw, Leslie A. THE IMPACT OF MEASUREMENT ERROR ON CONTINUOUS TIME PANEL MODELS.

Degree: MA, Psychology, 2015, University of Kansas

 Prior studies have shown that analyzing a continuous time panel model with the Exact Discrete Model (EDM) is less biased and more efficient than approximate… (more)

Subjects/Keywords: Quantitative psychology; bias; continuous time; differential equations; efficiency; measurement error; panel model

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APA (6th Edition):

Shaw, L. A. (2015). THE IMPACT OF MEASUREMENT ERROR ON CONTINUOUS TIME PANEL MODELS. (Masters Thesis). University of Kansas. Retrieved from http://hdl.handle.net/1808/19547

Chicago Manual of Style (16th Edition):

Shaw, Leslie A. “THE IMPACT OF MEASUREMENT ERROR ON CONTINUOUS TIME PANEL MODELS.” 2015. Masters Thesis, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/19547.

MLA Handbook (7th Edition):

Shaw, Leslie A. “THE IMPACT OF MEASUREMENT ERROR ON CONTINUOUS TIME PANEL MODELS.” 2015. Web. 20 Sep 2019.

Vancouver:

Shaw LA. THE IMPACT OF MEASUREMENT ERROR ON CONTINUOUS TIME PANEL MODELS. [Internet] [Masters thesis]. University of Kansas; 2015. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/19547.

Council of Science Editors:

Shaw LA. THE IMPACT OF MEASUREMENT ERROR ON CONTINUOUS TIME PANEL MODELS. [Masters Thesis]. University of Kansas; 2015. Available from: http://hdl.handle.net/1808/19547


University of Kansas

3. Lang, Kyle Matthew. MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net.

Degree: PhD, Psychology, 2015, University of Kansas

 Correctly specifying the imputation model when conducting multiple imputation remains one of the most significant challenges in missing data analysis. This dissertation introduces a robust… (more)

Subjects/Keywords: Quantitative psychology and psychometrics; Statistics; Bayesian Statistics; Big Data; Missing Data; Multiple Imputation; P >; N; Regularized Regression

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APA (6th Edition):

Lang, K. M. (2015). MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/19062

Chicago Manual of Style (16th Edition):

Lang, Kyle Matthew. “MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net.” 2015. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/19062.

MLA Handbook (7th Edition):

Lang, Kyle Matthew. “MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net.” 2015. Web. 20 Sep 2019.

Vancouver:

Lang KM. MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net. [Internet] [Doctoral dissertation]. University of Kansas; 2015. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/19062.

Council of Science Editors:

Lang KM. MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net. [Doctoral Dissertation]. University of Kansas; 2015. Available from: http://hdl.handle.net/1808/19062


University of Kansas

4. Shaw, Leslie A. The Role of Omitted Variables in Estimates for a Continuous Time Cross-Lag Panel Model.

Degree: PhD, Psychology, 2017, University of Kansas

 One assumption in regression-based models is that no theoretically important variables have been omitted from the model. Provided an omitted variable has a strong effect… (more)

Subjects/Keywords: Quantitative psychology; bias; exact discrete model; omitted variables; robust

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APA (6th Edition):

Shaw, L. A. (2017). The Role of Omitted Variables in Estimates for a Continuous Time Cross-Lag Panel Model. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/26026

Chicago Manual of Style (16th Edition):

Shaw, Leslie A. “The Role of Omitted Variables in Estimates for a Continuous Time Cross-Lag Panel Model.” 2017. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/26026.

MLA Handbook (7th Edition):

Shaw, Leslie A. “The Role of Omitted Variables in Estimates for a Continuous Time Cross-Lag Panel Model.” 2017. Web. 20 Sep 2019.

Vancouver:

Shaw LA. The Role of Omitted Variables in Estimates for a Continuous Time Cross-Lag Panel Model. [Internet] [Doctoral dissertation]. University of Kansas; 2017. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/26026.

Council of Science Editors:

Shaw LA. The Role of Omitted Variables in Estimates for a Continuous Time Cross-Lag Panel Model. [Doctoral Dissertation]. University of Kansas; 2017. Available from: http://hdl.handle.net/1808/26026


University of Kansas

5. Selig, James Patrick. Where has the time gone? The role of time lags in models for longitudinal data.

Degree: PhD, Psychology, 2009, University of Kansas

 The purpose of this dissertation is to draw attention to a long neglected, yet very important issue in the statistical modeling of longitudinal data. The… (more)

Subjects/Keywords: Psychology; Lags; Longitudinal

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APA (6th Edition):

Selig, J. P. (2009). Where has the time gone? The role of time lags in models for longitudinal data. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/5546

Chicago Manual of Style (16th Edition):

Selig, James Patrick. “Where has the time gone? The role of time lags in models for longitudinal data.” 2009. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/5546.

MLA Handbook (7th Edition):

Selig, James Patrick. “Where has the time gone? The role of time lags in models for longitudinal data.” 2009. Web. 20 Sep 2019.

Vancouver:

Selig JP. Where has the time gone? The role of time lags in models for longitudinal data. [Internet] [Doctoral dissertation]. University of Kansas; 2009. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/5546.

Council of Science Editors:

Selig JP. Where has the time gone? The role of time lags in models for longitudinal data. [Doctoral Dissertation]. University of Kansas; 2009. Available from: http://hdl.handle.net/1808/5546


University of Kansas

6. Lee, Ihno Ann. Temporal Mechanisms Underlying Systematic Mood Fluctuation: Re-evaluating Time and Day.

Degree: PhD, Psychology, 2011, University of Kansas

 Positive and negative moods fluctuate systematically during our waking hours and throughout the course of a week; however, the mechanisms underlying these changes have not… (more)

Subjects/Keywords: Social psychology; Quantitative psychology; Psychometrics; Affect; Entrainment; Mood fluctuation; Nonlinear change; Temporal influences

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APA (6th Edition):

Lee, I. A. (2011). Temporal Mechanisms Underlying Systematic Mood Fluctuation: Re-evaluating Time and Day. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/8158

Chicago Manual of Style (16th Edition):

Lee, Ihno Ann. “Temporal Mechanisms Underlying Systematic Mood Fluctuation: Re-evaluating Time and Day.” 2011. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/8158.

MLA Handbook (7th Edition):

Lee, Ihno Ann. “Temporal Mechanisms Underlying Systematic Mood Fluctuation: Re-evaluating Time and Day.” 2011. Web. 20 Sep 2019.

Vancouver:

Lee IA. Temporal Mechanisms Underlying Systematic Mood Fluctuation: Re-evaluating Time and Day. [Internet] [Doctoral dissertation]. University of Kansas; 2011. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/8158.

Council of Science Editors:

Lee IA. Temporal Mechanisms Underlying Systematic Mood Fluctuation: Re-evaluating Time and Day. [Doctoral Dissertation]. University of Kansas; 2011. Available from: http://hdl.handle.net/1808/8158


University of Kansas

7. Fall, Emily C. Modeling Heterogeneity in Indirect Effects: Multilevel Structural Equation Modeling Strategies.

Degree: PhD, Psychology, 2011, University of Kansas

 The heterogeneity implicit in much of social science research can be accommodated by using complex modeling procedures such as SEM or MLM. Ignoring heterogeneity, particularly… (more)

Subjects/Keywords: Quantitative psychology; Psychometrics; Cross-lagged panel model; Longitudinal modeling; Mediation; Multilevel structural equation modeling

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APA (6th Edition):

Fall, E. C. (2011). Modeling Heterogeneity in Indirect Effects: Multilevel Structural Equation Modeling Strategies. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/9787

Chicago Manual of Style (16th Edition):

Fall, Emily C. “Modeling Heterogeneity in Indirect Effects: Multilevel Structural Equation Modeling Strategies.” 2011. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/9787.

MLA Handbook (7th Edition):

Fall, Emily C. “Modeling Heterogeneity in Indirect Effects: Multilevel Structural Equation Modeling Strategies.” 2011. Web. 20 Sep 2019.

Vancouver:

Fall EC. Modeling Heterogeneity in Indirect Effects: Multilevel Structural Equation Modeling Strategies. [Internet] [Doctoral dissertation]. University of Kansas; 2011. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/9787.

Council of Science Editors:

Fall EC. Modeling Heterogeneity in Indirect Effects: Multilevel Structural Equation Modeling Strategies. [Doctoral Dissertation]. University of Kansas; 2011. Available from: http://hdl.handle.net/1808/9787


University of Kansas

8. Boulton, Aaron Jacob. Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data.

Degree: PhD, Psychology, 2014, University of Kansas

 Continuous-time models are used in many areas of science. However, in psychology and related fields, continuous-time models are often difficult to apply because only a… (more)

Subjects/Keywords: Quantitative psychology and psychometrics; Bayesian Statistics; Continuous Time; Exact Discrete Model; Panel Data

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APA (6th Edition):

Boulton, A. J. (2014). Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/16843

Chicago Manual of Style (16th Edition):

Boulton, Aaron Jacob. “Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data.” 2014. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/16843.

MLA Handbook (7th Edition):

Boulton, Aaron Jacob. “Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data.” 2014. Web. 20 Sep 2019.

Vancouver:

Boulton AJ. Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data. [Internet] [Doctoral dissertation]. University of Kansas; 2014. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/16843.

Council of Science Editors:

Boulton AJ. Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data. [Doctoral Dissertation]. University of Kansas; 2014. Available from: http://hdl.handle.net/1808/16843


University of Kansas

9. Harpole, Jared Kenneth. A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups.

Degree: PhD, Psychology, 2015, University of Kansas

 Multiple-indicator multiple cause (MIMIC) models have become a popular latent variable method to detect differential item functioning (DIF) by practitioners. The ease of including groups… (more)

Subjects/Keywords: Quantitative psychology; Psychology; Educational tests & measurements; Bayesian; Differential Item Functioning; MIMIC Model; Multiple Groups; Psychometrics; Structural Equation Modeling

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APA (6th Edition):

Harpole, J. K. (2015). A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/21697

Chicago Manual of Style (16th Edition):

Harpole, Jared Kenneth. “A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups.” 2015. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/21697.

MLA Handbook (7th Edition):

Harpole, Jared Kenneth. “A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups.” 2015. Web. 20 Sep 2019.

Vancouver:

Harpole JK. A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups. [Internet] [Doctoral dissertation]. University of Kansas; 2015. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/21697.

Council of Science Editors:

Harpole JK. A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups. [Doctoral Dissertation]. University of Kansas; 2015. Available from: http://hdl.handle.net/1808/21697


University of Kansas

10. Staggs, Vincent. Parametric Bootstrap Interval Approach to Inference for Fixed Effects in the Mixed Linear Model.

Degree: PhD, Psychology, 2009, University of Kansas

 In mixed models, empirical best linear unbiased estimators of fixed effects generally have mean square errors (MSEs) that cannot be written in closed form. Standard… (more)

Subjects/Keywords: Psychology; Psychometrics; Statistics; Bootstrap; Hierarchical linear model; Mixed model; Multilevel model

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APA (6th Edition):

Staggs, V. (2009). Parametric Bootstrap Interval Approach to Inference for Fixed Effects in the Mixed Linear Model. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/5513

Chicago Manual of Style (16th Edition):

Staggs, Vincent. “Parametric Bootstrap Interval Approach to Inference for Fixed Effects in the Mixed Linear Model.” 2009. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/5513.

MLA Handbook (7th Edition):

Staggs, Vincent. “Parametric Bootstrap Interval Approach to Inference for Fixed Effects in the Mixed Linear Model.” 2009. Web. 20 Sep 2019.

Vancouver:

Staggs V. Parametric Bootstrap Interval Approach to Inference for Fixed Effects in the Mixed Linear Model. [Internet] [Doctoral dissertation]. University of Kansas; 2009. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/5513.

Council of Science Editors:

Staggs V. Parametric Bootstrap Interval Approach to Inference for Fixed Effects in the Mixed Linear Model. [Doctoral Dissertation]. University of Kansas; 2009. Available from: http://hdl.handle.net/1808/5513


University of Kansas

11. Clark, John Michael, III. Aberrant Response Patterns as a Multidimensional Phenomenon: Using Factor-Analytic Model Comparison to Detect Cheating.

Degree: PhD, Psychology, 2010, University of Kansas

 This dissertation proposes a new factor-analytic technique for detecting cheating on exams. Person-fit statistics have been developed to assess the extent to which examinees' response… (more)

Subjects/Keywords: Quantitative psychology; Aberrant response patterns; Cheating; Factor analysis; Person-fit

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APA (6th Edition):

Clark, John Michael, I. (2010). Aberrant Response Patterns as a Multidimensional Phenomenon: Using Factor-Analytic Model Comparison to Detect Cheating. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/6943

Chicago Manual of Style (16th Edition):

Clark, John Michael, III. “Aberrant Response Patterns as a Multidimensional Phenomenon: Using Factor-Analytic Model Comparison to Detect Cheating.” 2010. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/6943.

MLA Handbook (7th Edition):

Clark, John Michael, III. “Aberrant Response Patterns as a Multidimensional Phenomenon: Using Factor-Analytic Model Comparison to Detect Cheating.” 2010. Web. 20 Sep 2019.

Vancouver:

Clark, John Michael I. Aberrant Response Patterns as a Multidimensional Phenomenon: Using Factor-Analytic Model Comparison to Detect Cheating. [Internet] [Doctoral dissertation]. University of Kansas; 2010. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/6943.

Council of Science Editors:

Clark, John Michael I. Aberrant Response Patterns as a Multidimensional Phenomenon: Using Factor-Analytic Model Comparison to Detect Cheating. [Doctoral Dissertation]. University of Kansas; 2010. Available from: http://hdl.handle.net/1808/6943


University of Kansas

12. Gu, Fei. Using Parametric and Residual-based Bootstrap to Assess the Absolute Goodness-of-fit for State Space Model.

Degree: PhD, Psychology & Research in Education, 2013, University of Kansas

 In this work, two types of bootstrap methods are used to evaluate the absolute goodness-of-fit for the linear state space model. The first bootstrap is… (more)

Subjects/Keywords: Quantitative psychology; Psychometrics

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APA (6th Edition):

Gu, F. (2013). Using Parametric and Residual-based Bootstrap to Assess the Absolute Goodness-of-fit for State Space Model. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/15100

Chicago Manual of Style (16th Edition):

Gu, Fei. “Using Parametric and Residual-based Bootstrap to Assess the Absolute Goodness-of-fit for State Space Model.” 2013. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/15100.

MLA Handbook (7th Edition):

Gu, Fei. “Using Parametric and Residual-based Bootstrap to Assess the Absolute Goodness-of-fit for State Space Model.” 2013. Web. 20 Sep 2019.

Vancouver:

Gu F. Using Parametric and Residual-based Bootstrap to Assess the Absolute Goodness-of-fit for State Space Model. [Internet] [Doctoral dissertation]. University of Kansas; 2013. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/15100.

Council of Science Editors:

Gu F. Using Parametric and Residual-based Bootstrap to Assess the Absolute Goodness-of-fit for State Space Model. [Doctoral Dissertation]. University of Kansas; 2013. Available from: http://hdl.handle.net/1808/15100


University of Kansas

13. Jorgensen, Terrence Dale. Selecting an Optimal Measurement Model and Detecting Differential Item Functioning Using Bayesian Confirmatory Factor Analysis.

Degree: PhD, Psychology, 2015, University of Kansas

 I investigated the sampling behavior of DIC and WAIC in the context of selecting an optimal measurement model in Bayesian SEM, as well as the… (more)

Subjects/Keywords: Quantitative psychology and psychometrics; Bayesian; confirmatory factor analysis; differential item functioning; measurement equivalence / invariance; structural equation modeling

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APA (6th Edition):

Jorgensen, T. D. (2015). Selecting an Optimal Measurement Model and Detecting Differential Item Functioning Using Bayesian Confirmatory Factor Analysis. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/19054

Chicago Manual of Style (16th Edition):

Jorgensen, Terrence Dale. “Selecting an Optimal Measurement Model and Detecting Differential Item Functioning Using Bayesian Confirmatory Factor Analysis.” 2015. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/19054.

MLA Handbook (7th Edition):

Jorgensen, Terrence Dale. “Selecting an Optimal Measurement Model and Detecting Differential Item Functioning Using Bayesian Confirmatory Factor Analysis.” 2015. Web. 20 Sep 2019.

Vancouver:

Jorgensen TD. Selecting an Optimal Measurement Model and Detecting Differential Item Functioning Using Bayesian Confirmatory Factor Analysis. [Internet] [Doctoral dissertation]. University of Kansas; 2015. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/19054.

Council of Science Editors:

Jorgensen TD. Selecting an Optimal Measurement Model and Detecting Differential Item Functioning Using Bayesian Confirmatory Factor Analysis. [Doctoral Dissertation]. University of Kansas; 2015. Available from: http://hdl.handle.net/1808/19054


University of Kansas

14. Garnier-Villarreal, Mauricio. Intra and Interindividual Variation Modeling: Bayesian Mixed-Effects Nonstationary Latent Differential Equation Model.

Degree: PhD, Psychology, 2016, University of Kansas

 Longitudinal analysis are powerful methods to estimate change over time. The combination of nomothetic and idiographic approaches within longitudinal analysis would allow to answer questions… (more)

Subjects/Keywords: Quantitative psychology; Bayesian; Latent Differential Equation; Mixed-effects

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APA (6th Edition):

Garnier-Villarreal, M. (2016). Intra and Interindividual Variation Modeling: Bayesian Mixed-Effects Nonstationary Latent Differential Equation Model. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/22394

Chicago Manual of Style (16th Edition):

Garnier-Villarreal, Mauricio. “Intra and Interindividual Variation Modeling: Bayesian Mixed-Effects Nonstationary Latent Differential Equation Model.” 2016. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/22394.

MLA Handbook (7th Edition):

Garnier-Villarreal, Mauricio. “Intra and Interindividual Variation Modeling: Bayesian Mixed-Effects Nonstationary Latent Differential Equation Model.” 2016. Web. 20 Sep 2019.

Vancouver:

Garnier-Villarreal M. Intra and Interindividual Variation Modeling: Bayesian Mixed-Effects Nonstationary Latent Differential Equation Model. [Internet] [Doctoral dissertation]. University of Kansas; 2016. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/22394.

Council of Science Editors:

Garnier-Villarreal M. Intra and Interindividual Variation Modeling: Bayesian Mixed-Effects Nonstationary Latent Differential Equation Model. [Doctoral Dissertation]. University of Kansas; 2016. Available from: http://hdl.handle.net/1808/22394

15. Short, Stephen David. Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance.

Degree: PhD, Psychology, 2014, University of Kansas

 Measurement invariance testing with confirmatory factor analysis has a long history in social science research, and more recently has increased use and popularity. The current… (more)

Subjects/Keywords: Quantitative psychology; Psychometrics; Factor analysis; Invariance; Longitudinal; Model fit; Power

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APA (6th Edition):

Short, S. D. (2014). Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/14570

Chicago Manual of Style (16th Edition):

Short, Stephen David. “Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance.” 2014. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/14570.

MLA Handbook (7th Edition):

Short, Stephen David. “Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance.” 2014. Web. 20 Sep 2019.

Vancouver:

Short SD. Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance. [Internet] [Doctoral dissertation]. University of Kansas; 2014. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/14570.

Council of Science Editors:

Short SD. Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance. [Doctoral Dissertation]. University of Kansas; 2014. Available from: http://hdl.handle.net/1808/14570

16. Harpole, Jared Kenneth. How Bandwidth Selection Algorithms Impact Exploratory Data Analysis Using Kernel Density Estimation.

Degree: MA, Psychology, 2013, University of Kansas

 Exploratory data analysis (EDA) is important, yet often overlooked in the social and behavioral sciences. Graphical analysis of one's data is central to EDA. A… (more)

Subjects/Keywords: Quantitative psychology; Psychometrics; Statistics; Bandwidth selection; Exploratory data analysis; Graphical analysis; Kernel density estimation

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APA (6th Edition):

Harpole, J. K. (2013). How Bandwidth Selection Algorithms Impact Exploratory Data Analysis Using Kernel Density Estimation. (Masters Thesis). University of Kansas. Retrieved from http://hdl.handle.net/1808/11725

Chicago Manual of Style (16th Edition):

Harpole, Jared Kenneth. “How Bandwidth Selection Algorithms Impact Exploratory Data Analysis Using Kernel Density Estimation.” 2013. Masters Thesis, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/11725.

MLA Handbook (7th Edition):

Harpole, Jared Kenneth. “How Bandwidth Selection Algorithms Impact Exploratory Data Analysis Using Kernel Density Estimation.” 2013. Web. 20 Sep 2019.

Vancouver:

Harpole JK. How Bandwidth Selection Algorithms Impact Exploratory Data Analysis Using Kernel Density Estimation. [Internet] [Masters thesis]. University of Kansas; 2013. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/11725.

Council of Science Editors:

Harpole JK. How Bandwidth Selection Algorithms Impact Exploratory Data Analysis Using Kernel Density Estimation. [Masters Thesis]. University of Kansas; 2013. Available from: http://hdl.handle.net/1808/11725

17. Pressman, Mindy. Who Exercises and When? The Effects of Intra- and Inter-Individual Variation on the Likelihood and Duration of Exercise.

Degree: MA, Psychology, 2013, University of Kansas

 The current study examined the ability of inter- and intra-individual characteristics to predict the likelihood and duration of exercise as well as mood. One hundred… (more)

Subjects/Keywords: Psychology; Exercise; Hostility; Sleep

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APA (6th Edition):

Pressman, M. (2013). Who Exercises and When? The Effects of Intra- and Inter-Individual Variation on the Likelihood and Duration of Exercise. (Masters Thesis). University of Kansas. Retrieved from http://hdl.handle.net/1808/14204

Chicago Manual of Style (16th Edition):

Pressman, Mindy. “Who Exercises and When? The Effects of Intra- and Inter-Individual Variation on the Likelihood and Duration of Exercise.” 2013. Masters Thesis, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/14204.

MLA Handbook (7th Edition):

Pressman, Mindy. “Who Exercises and When? The Effects of Intra- and Inter-Individual Variation on the Likelihood and Duration of Exercise.” 2013. Web. 20 Sep 2019.

Vancouver:

Pressman M. Who Exercises and When? The Effects of Intra- and Inter-Individual Variation on the Likelihood and Duration of Exercise. [Internet] [Masters thesis]. University of Kansas; 2013. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/14204.

Council of Science Editors:

Pressman M. Who Exercises and When? The Effects of Intra- and Inter-Individual Variation on the Likelihood and Duration of Exercise. [Masters Thesis]. University of Kansas; 2013. Available from: http://hdl.handle.net/1808/14204

18. Wang, Mian. Longitudinal Differential Item Functioning Detection Using Bifactor Models and the Wald Test.

Degree: PhD, Psychology, 2016, University of Kansas

 The use of longitudinal data for studying cross-time changes is built on the key assumption that properties (e.g., slopes and intercepts) of the repeatedly-used items… (more)

Subjects/Keywords: Quantitative psychology; bifactor; differential item functioning; longitudinal data; measurement invariance; wald test

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APA (6th Edition):

Wang, M. (2016). Longitudinal Differential Item Functioning Detection Using Bifactor Models and the Wald Test. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/22484

Chicago Manual of Style (16th Edition):

Wang, Mian. “Longitudinal Differential Item Functioning Detection Using Bifactor Models and the Wald Test.” 2016. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/22484.

MLA Handbook (7th Edition):

Wang, Mian. “Longitudinal Differential Item Functioning Detection Using Bifactor Models and the Wald Test.” 2016. Web. 20 Sep 2019.

Vancouver:

Wang M. Longitudinal Differential Item Functioning Detection Using Bifactor Models and the Wald Test. [Internet] [Doctoral dissertation]. University of Kansas; 2016. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/22484.

Council of Science Editors:

Wang M. Longitudinal Differential Item Functioning Detection Using Bifactor Models and the Wald Test. [Doctoral Dissertation]. University of Kansas; 2016. Available from: http://hdl.handle.net/1808/22484

19. Martin, David Matthew. Mindfulness and Attachment Security as Predictors of Sucess in Therapy.

Degree: PhD, Counseling Psychology, 2012, University of Kansas

 This work focuses on the role of mindfulness and attachment security as agents of change in successful therapy. Two studies were conducted to investigate the… (more)

Subjects/Keywords: Counseling psychology; Social psychology; Attachment security; Mindfulness; Psychotherapy

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APA (6th Edition):

Martin, D. M. (2012). Mindfulness and Attachment Security as Predictors of Sucess in Therapy. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/10127

Chicago Manual of Style (16th Edition):

Martin, David Matthew. “Mindfulness and Attachment Security as Predictors of Sucess in Therapy.” 2012. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/10127.

MLA Handbook (7th Edition):

Martin, David Matthew. “Mindfulness and Attachment Security as Predictors of Sucess in Therapy.” 2012. Web. 20 Sep 2019.

Vancouver:

Martin DM. Mindfulness and Attachment Security as Predictors of Sucess in Therapy. [Internet] [Doctoral dissertation]. University of Kansas; 2012. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/10127.

Council of Science Editors:

Martin DM. Mindfulness and Attachment Security as Predictors of Sucess in Therapy. [Doctoral Dissertation]. University of Kansas; 2012. Available from: http://hdl.handle.net/1808/10127

20. Pornprasertmanit, Sunthud. The Unified Approach for Model Evaluation in Structural Equation Modeling.

Degree: PhD, Psychology, 2014, University of Kansas

 Practical fit indices have been widely used for model fit evaluation in Structural Equation Modeling. This dissertation discusses the properties of the fit indices including… (more)

Subjects/Keywords: Quantitative psychology and psychometrics; Statistics; model fit; model parsimony; practical fit indices; structural equation modeling

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APA (6th Edition):

Pornprasertmanit, S. (2014). The Unified Approach for Model Evaluation in Structural Equation Modeling. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/16828

Chicago Manual of Style (16th Edition):

Pornprasertmanit, Sunthud. “The Unified Approach for Model Evaluation in Structural Equation Modeling.” 2014. Doctoral Dissertation, University of Kansas. Accessed September 20, 2019. http://hdl.handle.net/1808/16828.

MLA Handbook (7th Edition):

Pornprasertmanit, Sunthud. “The Unified Approach for Model Evaluation in Structural Equation Modeling.” 2014. Web. 20 Sep 2019.

Vancouver:

Pornprasertmanit S. The Unified Approach for Model Evaluation in Structural Equation Modeling. [Internet] [Doctoral dissertation]. University of Kansas; 2014. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1808/16828.

Council of Science Editors:

Pornprasertmanit S. The Unified Approach for Model Evaluation in Structural Equation Modeling. [Doctoral Dissertation]. University of Kansas; 2014. Available from: http://hdl.handle.net/1808/16828

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