Purpose: As measures of birth-assigned sex, gender identity, and perceived gender presentation are increasingly included in large-scale research studies, data analysis approaches incorporating such measures are needed. Large samples capable of demonstrating variation within the transgender and gender diverse (TGD) community can inform intervention efforts to improve health equity. A population-based sample of TGD youth was used to examine associations between perceived gender presentation, bullying victimization, and emotional distress using two data analysis approaches.

Methods: This secondary data analysis of the Minnesota Student Survey included 2168 9th and 11th graders who identified as "transgender, genderqueer, genderfluid, or unsure about their gender identity." Youth reported their biological sex, how others perceived their gender presentation, experiences of four forms of bullying victimization, and four measures of emotional distress. Logistic regression and multifactor analysis of variance (ANOVA) were used to compare and contrast two analysis approaches.

Results: Logistic regressions indicated that TGD youth perceived as more gender incongruent had higher odds of bullying victimization and emotional distress relative to those perceived as very congruent with their biological sex. Multifactor ANOVAs demonstrated more variable patterns and allowed for comparisons of each perceived presentation group with all other groups, reflecting nuances that exist within TGD youth.

Conclusion: Researchers should adopt data analysis strategies that allow for comparisons of all perceived gender presentation categories rather than assigning a reference group. Those working with TGD youth should be particularly attuned to youth perceived as gender incongruent as they may be more likely to experience bullying victimization and emotional distress.