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Analytical Comparison Of Contrasting Approaches To Estimating Competing Risks Models, Brian Stephen Rickard
Analytical Comparison Of Contrasting Approaches To Estimating Competing Risks Models, Brian Stephen Rickard
Graduate Theses and Dissertations
Survival analysis is a commonly used tool in many fields but has seen little use in education research despite a common number of research questions for which it is well suited. Researchers often use logistic regression instead; however, this omits useful information. In research on retention and graduation for example, the timing of the event is an important piece of information omitted when using logistic regression. A simulation study was conducted to evaluate four methods of analyzing competing risks survival data, Cox proportional hazards regression, Weibull regression, Fine and Gray's Method, and Cox proportional hazards regression with frailty. College student …
Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors, Riley K. Acton
Characteristics Of Stem Success: A Survival Analysis Model Of Factors Influencing Time To Graduation Among Undergraduate Stem Majors, Riley K. Acton
Business and Economics Honors Papers
Producing more graduates in Science, Technology, Engineering, and Mathematics (STEM), as well as ensuring students complete college in a timely manner are both areas of national public policy interest. In order to improve these two outcomes, it is imperative to understand what factors lead undergraduate students to persist in, and ultimately graduate with STEM degrees. This paper uses data from the Beginning Postsecondary Students Longitudinal Study, provided by The National Center of Education Statistics, to model the time to baccalaureate degree among STEM majors using a Cox proportional hazard model.