From the Research
Adjusting for variables like sex, low-income status, sexual orientation, school ownership, and region in generalized linear mixed models is justified because these factors can confound the relationship between meaningful interactional diversity and educational outcomes. These demographic and institutional characteristics often independently influence both the likelihood of experiencing diverse interactions and educational outcomes, potentially creating spurious associations if not controlled for. By including these variables in statistical models, researchers can isolate the unique contribution of interactional diversity to educational outcomes while accounting for systematic differences across student populations and institutional contexts. This adjustment helps eliminate alternative explanations for observed relationships and increases confidence that any identified associations between diversity experiences and outcomes are not merely reflections of pre-existing differences among students or institutions. Additionally, controlling for these variables allows researchers to determine whether diversity experiences benefit students equally across different demographic groups and institutional settings, providing more nuanced insights into how diversity initiatives might be tailored to maximize educational benefits for all students. According to the most recent study on the topic, 1, generalized linear mixed models can be used to select both fixed and random effects, which supports the use of these models in adjusting for variables like sex, low-income status, sexual orientation, school ownership, and region.
Some key points to consider when justifying the adjustment for these variables include:
- The potential for confounding variables to create spurious associations between meaningful interactional diversity and educational outcomes
- The importance of accounting for systematic differences across student populations and institutional contexts
- The need to eliminate alternative explanations for observed relationships and increase confidence in identified associations
- The ability to determine whether diversity experiences benefit students equally across different demographic groups and institutional settings
By considering these points and using generalized linear mixed models to adjust for variables like sex, low-income status, sexual orientation, school ownership, and region, researchers can gain a more nuanced understanding of the relationship between meaningful interactional diversity and educational outcomes, and make more informed decisions about how to tailor diversity initiatives to maximize educational benefits for all students, as discussed in 2, 3, 4, and 5.