title: Multivariate parametric random effect regression models for fecundability studies.
abstract: Delay until conception is generally described by a mixture of geometric distributions. Weinberg and Gladen (1986, Biometrics 42, 547-560) proposed a regression generalization of the beta-geometric mixture model where covariates effects were expressed in terms of contrasts of marginal hazards. Scheike and Jensen (1997, Biometrics 53, 318-329) developed a frailty model for discrete event times data based on discrete-time analogues of Hougaard's results (1984, Biometrika 71, 75-83). This paper is on a generalization to a three-parameter family distribution and an extension to multivariate cases. The model allows the introduction of explanatory variables, including time-dependent variables at the subject-specific level, together with a choice from a flexible family of random effect distributions. This makes it possible, in the context of medically assisted conception, to include data sources with multiple pregnancies (or attempts at pregnancy) per couple.
authors: Unité de Biostatistiques, Département d'Information Médicale des Hospices Civils de Lyon, 162 Avenue Lacassagne, 69424 Lyon, France. rene.ecochard@chu-lyon.fr
authors: R
authors: R
authors: Ecochard
authors: D G
authors: DG
authors: Clayton
mesh_terms: D001699:Biometry / Q000379:methods; D005260:Female; D005298:Fertility; D006801:Humans; D007316:Insemination, Artificial, Heterologous; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D015999:Multivariate Analysis; D009845:Oligospermia; D011247:Pregnancy; D012044:Regression Analysis