On the performance of random‐coefficient pattern‐mixture models for non‐ignorable drop‐out
On the performance of random‐coefficient pattern‐mixture models for non‐ignorable drop‐out
Abstract Random‐coefficient pattern‐mixture models (RCPMMs) have been proposed for longitudinal data when drop‐out is thought to be non‐ignorable. An RCPMM is a random‐effects model with summaries of drop‐out time included among the regressors. The basis of every RCPMM is extrapolation. We review RCPMMs, describe various extrapolation strategies, and show how …