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Uppsala University

1. Vele, Lutendo. ANALYSIS OF BINARY DEPENDENT VARIABLES USING LINEAR PROBABILITY MODEL AND LOGISTIC REGRESSION: A REPLICATION STUDY.

Degree: Statistics, 2019, Uppsala University

Linear Probability Model (LPM) is commonly used because it is easy to compute and interpret than with logits and probits even though the estimated probabilities may fall outside the \big[0,1\big] interval and the linearity concept does not make much sense when dealing with probabilities. This paper extends upon the results of \citeA{Dara} reviewing the use of LPM to examine if alcohol prohibition reduces domestic violence. Regular LPM resulted in inconclusive estimates since prohibition was omitted due to collinearity as controls were added. However \citeA{Dara} had results, and further inspection on their regression commands showed that they ran a linear regression, then a post-estimation on residuals and further used residuals as a dependent variable hence the results were different from the regular LPM. Their method still resulted in unbounded predicted probabilities and heteroscedastic residuals, thus showing that OLS was inefficient and a non-linear binary choice model like logistic regression would be a better option. Logistic regression predicts the probability of an outcome that can only have two values and was therefore used in this paper. Unlike LPM, logistic regression uses a non-linear function which results in a sigmoid bounding the predicted outcome between 0 and 1. Logistic regression had no complication; thus logistic (or any another non-linear dichotomous dependent variable models) regression should have been used on the final analysis while LPM is used at a preliminary stage to get quick results.

Subjects/Keywords: binary choice models; logistic regression; linear probability model; forbidden regression; binary dependent variables; dichotomous variables; residuals as dependent variables; Economics; Nationalekonomi; Other Natural Sciences; Annan naturvetenskap

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

APA (6th Edition):

Vele, L. (2019). ANALYSIS OF BINARY DEPENDENT VARIABLES USING LINEAR PROBABILITY MODEL AND LOGISTIC REGRESSION: A REPLICATION STUDY. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385535

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

Chicago Manual of Style (16th Edition):

Vele, Lutendo. “ANALYSIS OF BINARY DEPENDENT VARIABLES USING LINEAR PROBABILITY MODEL AND LOGISTIC REGRESSION: A REPLICATION STUDY.” 2019. Thesis, Uppsala University. Accessed March 08, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385535.

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

MLA Handbook (7th Edition):

Vele, Lutendo. “ANALYSIS OF BINARY DEPENDENT VARIABLES USING LINEAR PROBABILITY MODEL AND LOGISTIC REGRESSION: A REPLICATION STUDY.” 2019. Web. 08 Mar 2021.

Vancouver:

Vele L. ANALYSIS OF BINARY DEPENDENT VARIABLES USING LINEAR PROBABILITY MODEL AND LOGISTIC REGRESSION: A REPLICATION STUDY. [Internet] [Thesis]. Uppsala University; 2019. [cited 2021 Mar 08]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385535.

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

Council of Science Editors:

Vele L. ANALYSIS OF BINARY DEPENDENT VARIABLES USING LINEAR PROBABILITY MODEL AND LOGISTIC REGRESSION: A REPLICATION STUDY. [Thesis]. Uppsala University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385535

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


University of New Mexico

2. Medina, Una E. MADD MESSAGE EFFECTS: A TWELVE-YEAR RANDOMIZED TRIAL.

Degree: Department of Communication and Journalism, 2010, University of New Mexico

One out of three Americans undergoes drunk-driving crashes; 23% result in death. To deter DWIs (Driving While under Influence), MADD (Mothers Against Drunk Drivers) created VIPs (Victim Impact Panels) where victims impact offenders with gory stories, photos, and threats of punishments and loss of freedom, hoping this message will deter DWIs. It is remarkable that although the VIP message is considered a primary DWI intervention, yet no studies have investigated VIP message effects. VIP message effects, their persistence and decay, are chronicled here over the course of 12 years. This study extends an empirical investigation of VIPs, conducted by Woodall, Delaney, Rogers, and Wheeler (2007) (n = 833) during 1994-1996. At 2 years, these researchers found MADD VIP participants' recidivism rates were 30% higher than their DWI School comparison group, trending toward significance at p = .0583. This study supports those results as significant at 12 years. As an extension, it investigates whether reactance theory explains VIP message effects failure. Reactance theory research, a subset of message effects research, explains how emotional, confrontational, and threatening messages induce psychological reactance in the mind of the message receiver, who then seeks to preserve his or her sense of freedom by behaving contrarily (Brehm, 1966). Hierarchically intensifying effects of these theoretical reactance antecedents are studied here in an unusual manner, as they occur in vivo, in real life. The same intervention was observed to have different effects depending on prior conditions and demographics. The emotional high-threat, high-confrontation MADD VIP message coincided with significantly shorter time to recidivism (p = .009, d = 1.64) and significantly higher number of subsequent arrests (p < .0001, d = 1.64) among recent prior offenders, and those with no priors under age 30 (p = .01, d = 0.35). Younger offenders may be associated with more iconoclastic behavior than older offenders (Beirness & Simpson, 1997; Greenberg, 2005; NHTSA, 2008), partially explaining the under-30 age effect. This study furthers persuasive message design as a science and suggests a message-based approach to intervention analysis. There was no effect when MADD VIP was analyzed simply as an intervention. However, there were highly significant effect sizes when the same MADD VIP intervention was analyzed as a message. This study concludes by offering MADD VIP best practice recommendations. Advisors/Committee Members: Woodall, W. Gill, Schuetz, Janice, Rivera, Mario A., McDermott, Virginia, Delaney, Harold.

Subjects/Keywords: Victim Impact panels; MADD; message effects; randomized trial; effect size; drunk driving; DWI; efficacy trial; method problems; methodological problems; communication theory; theory building; rhetorical analysis; triangulation; drunk driving; interventions; covariates; ANOVA; ANCOVA; survival analysis; message context; message content; message function; message intensity; message frequency; message metrics; message pathos; pathos; message decay; decay rate; message decay rate; intent to persuade; persuasion; confrontation; shame; shaming; public shaming; public censure; forewarning; perceived threat; reactance theory; assumptions; sampling error; recruitment error; non-adherence to condition; random assignment error; factorial design; operationalization; theory construct operationalization; methods informed by literature; methodological symbiosis; questionnaire reliability and validity; secondary data sources; public arrest record; public data; covariate operationalization; reactance constructs; content analysis; theme analysis; prior arrest; censored cases; QSR N6; SPSS; Excel; limitations; under-identification; attrition; population attrition; bimodal distribution; dichotomous variables; data splitting; discretizing data; time to recidivism; subsequent arrests; emotional change; emotion score; outliers; reactance antecedent; message dose; message dosage; treatment fidelity; assess treatment fidelity; predictor variables; controlling variables; demographic covariate; demographic predictor; confirmation bias; data bias; interaction effect; treatment effect; message design; fear appeal; message strength; anger; survival analysis; time dependence; mixed methods; study design; message standardization; internal validity; hard data; hard end-point data; marginal sample size; observed variables; intervening factors; intervening variables; sample size; in vivo; hierarchy of effects; emotional threat; older offenders; young offenders; intervention analysis; message-based approach; best practices; DWI intervention; DWI treatment; prior conditions; iconoclast; Drunks Against MADD Mothers; resistance; message design science

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

APA (6th Edition):

Medina, U. E. (2010). MADD MESSAGE EFFECTS: A TWELVE-YEAR RANDOMIZED TRIAL. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/12395

Chicago Manual of Style (16th Edition):

Medina, Una E. “MADD MESSAGE EFFECTS: A TWELVE-YEAR RANDOMIZED TRIAL.” 2010. Doctoral Dissertation, University of New Mexico. Accessed March 08, 2021. http://hdl.handle.net/1928/12395.

MLA Handbook (7th Edition):

Medina, Una E. “MADD MESSAGE EFFECTS: A TWELVE-YEAR RANDOMIZED TRIAL.” 2010. Web. 08 Mar 2021.

Vancouver:

Medina UE. MADD MESSAGE EFFECTS: A TWELVE-YEAR RANDOMIZED TRIAL. [Internet] [Doctoral dissertation]. University of New Mexico; 2010. [cited 2021 Mar 08]. Available from: http://hdl.handle.net/1928/12395.

Council of Science Editors:

Medina UE. MADD MESSAGE EFFECTS: A TWELVE-YEAR RANDOMIZED TRIAL. [Doctoral Dissertation]. University of New Mexico; 2010. Available from: http://hdl.handle.net/1928/12395

.