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应用于比较生育力研究的贝塔-几何分布。

The beta-geometric distribution applied to comparative fecundability studies.

作者信息

Weinberg C R, Gladen B C

出版信息

Biometrics. 1986 Sep;42(3):547-60.

PMID:3567288
Abstract

A convenient measure of fecundability is time (number of menstrual cycles) required to achieve pregnancy. Couples attempting pregnancy are heterogeneous in their per-cycle probability of success. If success probabilities vary among couples according to a beta distribution, then cycles to pregnancy will have a beta-geometric distribution. Under this model, the inverse of the cycle-specific conception rate is a linear function of time. Data on cycles to pregnancy can be used to estimate the beta parameters by maximum likelihood in a straightforward manner with a package such as GLIM. The likelihood ratio test can thus be employed in studies of exposures that may impair fecundability. Covariates are incorporated in a natural way. The model is illustrated by applying it to data on cycles to pregnancy in smokers and nonsmokers, with adjustment for covariates. For a cross-sectional study, when length-biased sampling is taken into account, the pre-interview attempt time is shown to follow a beta-geometric distribution, so that the same methods of analysis can be applied even though all of the available data are right-censored. For a cohort followed prospectively, there will be some couples enrolled whose fecundability is effectively 0, and for such applications, the beta could be considered to be contaminated by a distribution degenerate at 0. The mixing parameter (proportion sterile) can be estimated by application of the expectation-maximization (EM) algorithm. This, too, can be carried out using GLIM.

摘要

衡量生育力的一个便捷指标是怀孕所需的时间(月经周期数)。尝试怀孕的夫妇每个周期的成功概率各不相同。如果夫妇之间的成功概率根据贝塔分布而变化,那么怀孕所需的周期将具有贝塔 - 几何分布。在这个模型下,特定周期受孕率的倒数是时间的线性函数。怀孕周期的数据可以使用诸如GLIM之类的软件包,通过最大似然法直接估计贝塔参数。因此,似然比检验可用于研究可能损害生育力的暴露因素。协变量以自然的方式纳入模型。通过将该模型应用于吸烟者和非吸烟者怀孕周期的数据,并对协变量进行调整,来说明该模型。对于横断面研究,当考虑到长度偏倚抽样时,访谈前的尝试时间显示遵循贝塔 - 几何分布,因此即使所有可用数据都是右删失的,也可以应用相同的分析方法。对于前瞻性队列研究,会有一些登记入组的夫妇其生育力实际上为0,对于此类应用,可以认为贝塔分布被退化到0的分布所污染。混合参数(不育比例)可以通过应用期望最大化(EM)算法来估计。这也可以使用GLIM来完成。

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