Raymond Michel, Turek Daniel, Crochet Pierre-André
Institut des Sciences de l'Evolution, University of Montpellier, CNRS, EPHE, IRD, place E. Bataillon, 34095, Montpellier, France.
Department of Mathematics, Lafayette College, Easton, PA, USA.
Arch Sex Behav. 2025 Jan;54(1):23-34. doi: 10.1007/s10508-024-02820-w. Epub 2024 Mar 4.
Research on the biological determinants of male homosexual preference has long realized that the older brother effect (FBOE, i.e., a higher fraternal birth rank of homosexuals) and the antagonist effect (AE, i.e., more fertile women have a higher chance of having a homosexual son) can both generate family data where homosexual men have more siblings and more older siblings than heterosexual men. Various statistical approaches were proposed in the recent literature to evaluate whether the action of FBOE or AE could be discriminated from empirical data, by controlling for the other effect. Here, we used simulated data to formally compare all the approaches that we could find in the relevant literature for their ability to reject the null hypothesis in the presence of a specified alternative hypothesis (tests based on regression, Bayesian modeling, or contingency tables). When testing for the FBOE, the relative performance of the different tests was different depending on the specific function generating the older brother effect. Even if no tests were found to always perform better than the others, some tests performed systematically poorly, and some tests displayed a systematic high rate of type-I error. For testing the AE, the relative performance of the tests was generally not changed across all parameter values assayed, providing a clear ranking of the various proposed approaches. Pros and cons for each candidate test are discussed, taking into consideration power and the rate of type-I error but also practicability, the possibility to control for confounding variables, and to consider alternative hypotheses.
对男性同性恋偏好的生物学决定因素的研究早就认识到,哥哥效应(FBOE,即同性恋者的兄弟出生顺序较高)和拮抗效应(AE,即生育能力较强的女性生育同性恋儿子的几率更高)都会产生这样的家庭数据:同性恋男性比异性恋男性有更多的兄弟姐妹,尤其是更多的哥哥。最近的文献中提出了各种统计方法,通过控制另一种效应来评估是否可以从经验数据中区分FBOE或AE的作用。在这里,我们使用模拟数据正式比较了我们在相关文献中找到的所有方法,看它们在存在特定备择假设的情况下拒绝原假设的能力(基于回归、贝叶斯建模或列联表的检验)。在检验FBOE时,不同检验的相对性能因产生哥哥效应的具体函数而异。即使没有发现哪种检验总是比其他检验表现更好,但有些检验系统地表现不佳,有些检验则显示出系统性的I型错误率很高。对于检验AE,在所有测定的参数值范围内,检验的相对性能通常没有变化,这为各种提出的方法提供了一个明确的排名。我们讨论了每个候选检验的优缺点,考虑了检验效能和I型错误率,还考虑了实用性、控制混杂变量的可能性以及考虑备择假设的可能性。