  This investigation examines the efficacy of multilevel analysis of individual
heterogeneity and discriminatory accuracy (MAIHDA) over fixed effect models
when performing intersectional studies. The research questions are: 1) What are
typical strata representation rates and outcomes on physics research-based
assessments? 2) To what extent do MAIHDA models create more accurate predicted
strata outcomes than fixed effects models? 3) To what extent do MAIHDA models
allow the modeling of smaller strata sample sizes? We simulated 3,000 datasets
based on real-world data from 5,955 students on the LASSO platform. We found
that MAIHDA created more accurate and precise predictions than fixed effect
models. We also found that using MAIHDA could allow researchers to disaggregate
their data further, creating smaller group sample sizes while maintaining more
accurate findings than fixed effect models. We recommend using MAIHDA over
fixed effect models for intersectional investigations.
