Pattern–Mixture Models with Incomplete Informative Cluster Size: Application to a Repeated Pregnancy Study
Ashok K. Chaurasia, Danping Liu, Paul S. Albert · Journal of the Royal Statistical Society Series C (Applied Statistics) · 2017
The incomplete informative cluster size problem is motivated by the NICHD Consecutive Pregnancies Study, aiming to study the relationship between pregnancy outcomes and parity. These pregnancy outcomes are potentially associated with the number of births over a woman's lifetime, resulting in an incomplete informative cluster size (censored at the end of the study window). We develop a pattern mixture model for informative cluster size by treating the lifetime number of births as a latent variable. We compare this approach with a simple alternative method that approximates the pattern mixture model. We show that the latent variable approach possesses good statistical properties for estimating both the mean trajectory of birthweight and the proportion of gestational hypertension with increasing parity.