A Current Approach to Logistic Regression Analysis of Birth Order and Sexual Orientation

Numerous statistical procedures have been developed to examine the statistical relations between quantifiable aspects of an individual's sibship and the likelihood of that individual manifesting a homosexual preference. Our purpose in this methodological paper is explaining how to use and how to interpret the multiple regression approach introduced by Ablaza et al. (2022), modified by Blanchard (2022), and reorganized by Zdaniuk et al. (2025)-hereafter, the ABZ model. First, we list the sibship variables of present interest (e.g., number of older brothers), summarize their previously observed associations with sexual orientation, and discuss the language and labels that we recommend for describing empirical results in this research area. We then explain, in concrete, practical terms, how to analyze these sibship variables using the ABZ method, and we present a model analysis using previously published data. Our subsequent sections, which go more deeply into the topic, include a discussion of the mathematical-statistical rationale behind the Ablaza et al. approach-more specifically, its foundation on the ceteris paribus condition of multiple regression in conjunction with a "subsetting" property of the relevant sibship data. Finally, we compare the performance of the ABZ model with an older, more frequently used logistic regression model, and we discuss the potential application of the ABZ model to outcomes other than homosexuality.