A mixed effects model for the analysis of ordinal longitudinal pain data subject to informative drop-out

We extend the model of Pulkstenis et al. that models binary longitudinal da ta, subject to informative drop-out through remedication, to the ordinal re sponse case. We present a selection model shared-parameter approach that sp ecifies mixed models for both ordinal response and discrete survival time t o remedication. In this fashion, the random parameter present in both model s completely characterizes the relationship between response and time to re medication inducing their conditional independence. With a log-log link fun ction for both response and study 'survival', as well as specification of a log-gamma distribution for the random effect, we obtain a closed-form expr ession for the marginal log-likelihood of response and time to remedication that does not require approximation or numerical integration techniques. A data analysis is performed and simulation results presented which support the consistency of parameter and standard error estimates. Copyright (C) 20 01 John Wiley & Sons, Ltd.