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Full-Text Articles in Psychology
Unpacking The Internalized Homonegativity–Health Relationship: How The Measurement Of Ih And Health Matter And The Contribution Of Religiousness, G. Tyler Lefevor, Eric R. Larsen, Rachel M. Golightly, Maddie Landrum
Unpacking The Internalized Homonegativity–Health Relationship: How The Measurement Of Ih And Health Matter And The Contribution Of Religiousness, G. Tyler Lefevor, Eric R. Larsen, Rachel M. Golightly, Maddie Landrum
Psychology Faculty Publications
Internalized homonegativity (IH) is widely recognized to negatively influence the health of lesbian, gay, bisexual, and queer/questioning (LGBQ +) individuals. It is not clear, however, the role that religiousness may play in the relationship between IH and health or how differing conceptualizations of IH or health may influence this relationship. We conducted a multi-level meta-analysis of 151 effect sizes from 68 studies to examine the relationship between IH and health as well as what may moderate this relationship. Results suggested that IH was consistently and negatively related to health (r = − .28). Analyses suggest that IH was most …
Efficient Exploration Of Many Variables And Interactions Using Regularized Regression, Tyson S. Barrett, Ginger Lockhart
Efficient Exploration Of Many Variables And Interactions Using Regularized Regression, Tyson S. Barrett, Ginger Lockhart
Psychology Faculty Publications
The prevention sciences often face several situations that can compromise the statistical power and validity of a study. Among these, research can (1) have data with many variables, sometimes with low sample sizes, (2) have highly correlated predictors, (3) have unclear theory or empirical evidence related to the research questions, and/or (4) have difficulty selecting the proper covariates in observational studies. Modeling in these situations is difficult—and at times impossible—with conventional methods. Fortunately, regularized regression—a machine learning technique—can aid in exploring datasets that are otherwise difficult to analyze, allowing researchers to draw insights from these data. Although many of these …