Factors on COVID-19 Pandemic-Related Sleep Disturbance for College Students: A Mixture Regression Analysis (Poster 44)

• In Event: Sunday Poster Session 1:15 pm
  In Poster Session: Educational Statisticians SIG Poster Session

iPresentation URL: https://aera24-aera.ipostersessions.com/Default.aspx?s=60-5D-AD-FA-AF-A5-83-B7-63-22-07-C7-E5-24-B6-FD

Abstract

Recent findings suggest that COVID-19 pandemic-related sleep disturbance is common to college students but not uniformly nor universally. Given the heterogeneity of effects of the pandemic on sleep, a mixture regression model is appropriate to study college students’ sleep quality. We used the Pittsburgh Sleep Quality Index (PSQI) to assess sleep before and during the COID-19 pandemic. A number of statistical indices including a novel approach, likelihood increment percentage (LIP) and likelihood increment percentage per parameter (LIPpp), were used to determine the number of latent groups. Our results suggested a more empirically justifiable representation of two groups, “typical college sleepers” and “disordered college sleepers.” Moreover, we found several demographic and academic factors impacted the two groups differently.

Authors

• Min Liu, Baylor University

• Tracy Trevorrow, Chaminade University