Dynamic prediction in fertility
Survival Analysis Theme
Abstract: Dynamic prediction of time-to-pregnancy is challenging due to unobserved patient heterogeneity. As over time couples with better prognoses become pregnant, those remaining behind represent a selected group with relatively poor prognoses. This selection process is not well captured by standard survival models. In this talk, I will present two models that explicitly account for unobserved heterogeneity. In the first, the beta-geometric model is used to make repeated predictions of natural conception over time. In the second, I use frailty models to evaluate the impact of heterogeneity on treatment delay. The predictions from these models can support treatment decisions of subfertility couples during their long and stressful journey towards parenthood.