Date of Award:
Doctor of Philosophy (PhD)
Developmental and prevention researchers aim to determine how unhealthy behaviors emerge. Mediation analysis offers a statistical tool that allows researchers to describe the processes underlying early risk and later health outcomes. Among existing longitudinal mediation models, latent difference score mediation stands out due to its unique ability to capture variations in changes both within and across individuals, as well as its ability to examine non-linear change over time. However, the literature currently lacks sample size guidelines for latent difference mediation models, which has proven to make the use of these models difficult. The current project addresses this limitation by offering an empirical set of sample guidelines for a variety of latent difference mediation score models through a Monte Carlo simulation study. By offering empirical sample size guidelines for latent difference score mediation models, future developmental and prevention researchers can make informed sampling decisions prior to data collection.
Moreover, women who misuse alcohol have been found to experience more severe medical consequences than men. However, minimal research has evaluated how gender specific risk factors influence its onset. The current project addresses this limitation by applying latent difference score mediation to evaluate how disordered eating behaviors among adolescent girls influence alcohol misuse among adult women.
Simone, Melissa, "Latent Difference Score Mediation Analysis in Developmental Research: A Monte Carlo Study and Application" (2018). All Graduate Theses and Dissertations. 7061.
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