The ‘heritability’ of a phenotype measures the proportion of trait variance due to genetic factors in a population. In the past 50 years, studies with monozygotic and dizygotic twins have estimated heritability for 17,804 traits;¹ thus twin studies are popular for estimating heritability. Researchers are often interested in estimating heritability for non‐normally distributed outcomes such as binary, counts, skewed or heavy‐tailed continuous traits. In these settings, the traditional normal ACE model (NACE) and Falconer's method can produce poor coverage of the true heritability. Therefore, we propose a robust generalized estimating equations (GEE2) framework for estimating the heritability of non‐normally distributed outcomes. The traditional NACE and Falconer's method are derived within this unified GEE2 framework, which additionally provides robust standard errors. Although the traditional Falconer's method cannot adjust for covariates, the corresponding ‘GEE2‐Falconer’ can incorporate mean and variance‐level covariate effects (e.g. let heritability vary by sex or age). Given a non‐normally distributed outcome, the GEE2 models are shown to attain better coverage of the true heritability compared to traditional methods. Finally, a scenario is demonstrated where NACE produces biased estimates of heritability while Falconer remains unbiased. Therefore, we recommend GEE2‐Falconer for estimating the heritability of non‐normally distributed outcomes in twin studies.

中文翻译：

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使用广义估计方程估计双胞胎研究中的遗传力的强大而统一的框架。

表型的“遗传力”衡量了种群中遗传因素导致的性状变异的比例。在过去的 50 年中，对同卵双胞胎和异卵双胞胎的研究估计了 17,804 个性状的遗传性；¹因此，双胞胎研究在估计遗传力方面很受欢迎。研究人员通常对估计非正态分布结果的遗传力感兴趣，例如二元、计数、偏斜或重尾连续性状。在这些设置中，传统的正态 ACE 模型 (NACE) 和 Falconer 方法可能会产生较差的真实遗传力覆盖率。因此，我们提出了一个强大的广义估计方程（GEE2）框架来估计非正态分布结果的遗传力。传统的 NACE 和 Falconer 的方法是在这个统一的 GEE2 框架内派生的，它另外提供了强大的标准误差。尽管传统的 Falconer 方法无法调整协变量，但相应的“GEE2-Falconer”可以结合均值和方差水平的协变量效应（例如 让遗传力因性别或年龄而异）。鉴于非正态分布的结果，与传统方法相比，GEE2 模型可以更好地覆盖真实的遗传力。最后，演示了一个场景，其中 NACE 产生了有偏差的遗传力估计，而 Falconer 保持无偏差。因此，我们推荐 GEE2-Falconer 来估计双胞胎研究中非正态分布结果的遗传力。