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Longitudinal random effects models for genetic analysis of binary data with application to mastitis in dairy cattle

机译：纵向二元数据遗传分析的随机效应模型及其在奶牛乳腺炎中的应用

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A Bayesian analysis of longitudinal mastitis records obtained in the course of lactation was undertaken. Data were 3341 test-day binary records from 329 first lactation Holstein cows scored for mastitis at 14 and 30 days of lactation and every 30 days thereafter. First, the conditional probability of a sequence for a given cow was the product of the probabilities at each test-day. The probability of infection at time t for a cow was a normal integral, with its argument being a function of "fixed" and "random" effects and of time. Models for the latent normal variable included effects of: (1) year-month of test + a five-parameter linear regression function ("fixed", within age-season of calving) + genetic value of the cow + environmental effect peculiar to all records of the same cow + residual. (2) As in (1), but with five parameter random genetic regressions for each cow. (3) A hierarchical structure, where each of three parameters of the regression function for each cow followed a mixed effects linear model. Model 1 posterior mean of heritability was 0.05. Model 2 heritabilities were: 0.27, 0.05, 0.03 and 0.07 at days 14, 60, 120 and 305, respectively. Model 3 heritabilities were 0.57, 0.16, 0.06 and 0.18 at days 14, 60, 120 and 305, respectively. Bayes factors were: 0.011 (Model 1/Model 2), 0.017 (Model 1/Model 3) and 1.535 (Model 2/Model 3). The probability of mastitis for an "average" cow, using Model 2, was: 0.06, 0.05, 0.06 and 0.07 at days 14, 60, 120 and 305, respectively. Relaxing the conditional independence assumption via an autoregressive process (Model 2) improved the results slightly.
机译：进行了在泌乳过程中获得的纵向乳腺炎记录的贝叶斯分析。数据是来自329例首次泌乳的荷斯坦奶牛在哺乳14天和30天以及之后每30天对乳腺炎评分的3341试验日二进制记录。首先，给定母牛的序列条件概率是每个测试日概率的乘积。母牛在时间t感染的概率是一个正常的积分，其论据是“固定”和“随机”效应以及时间的函数。潜在正常变量的模型包括以下影响：（1）试验的年月+五参数线性回归函数（在产犊年龄季节内为“固定”）+母牛的遗传价值+所有动物特有的环境影响同一头牛的记录+残差。 （2）和（1）一样，但是每头母牛有五个参数随机遗传回归。 （3）分层结构，其中每头母牛的回归函数的三个参数中的每个参数都遵循混合效应线性模型。模型1的遗传后验平均值为0.05。模型2的遗传力在第14、60、120和305天分别为0.27、0.05、0.03和0.07。在第14、60、120和305天，模型3的遗传力分别为0.57、0.16、0.06和0.18。贝叶斯系数为：0.011（模型1 /模型2），0.017（模型1 /模型3）和1.535（模型2 /模型3）。使用模型2，“平均”母牛患乳腺炎的概率分别在第14、60、120和305天分别为0.06、0.05、0.06和0.07。通过自回归过程（模型2）放宽条件独立性假设可以稍微改善结果。

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