Statistical analysis of outcomes from repeated pregnancies: effects of HLA sharing on fetal loss rates

As part of our ongoing studies of genetic markers of reproductive outcome in the Hutterites, we have been analyzing potential risk factors for pregnancy outcomes. In particular, we are interested in the effects of HLA sharing between parents on fetal loss rates. Pregnancy outcome data such as these have two characteristics that create statistical challenges, i.e., repeated observations per couple and between-couple heterogeneity in risk. We critically examine four approaches based on the logistic model for the analysis of this and similar data: 1) unconditional likelihood analysis with and without fixed cluster effects; 2) conditional likelihood analysis; 3) mixed-effects analysis with random cluster effects; and 4) the robust generalized estimating equation (GEE) procedure. Of these approaches, the GEE method of Liang and Zeger would be best suited for the analysis of our data when the question of interest concerns a variable that is constant over all pregnancies, such as HLA sharing. If the question concerns a couple's risk associated with a changing variable such as maternal age, the mixed-effects analysis is the more appropriate.