Abstract
A model is presented for the measurement of change of quality of life in clinical trials with time under the influence of one or more treatments. Quality of life is regarded as a multidimensional latent variable, and is measured through dichotomous item responses on a number of points in time. Change of quality of life is ‘explained’ with a latent logistic regression model which may include parameters for the time process, the effects of clinical treatments, and interaction parameters. By assuming the absence of patient/time interaction within treatment groups, the parameters of the time process and the treatment effects can be estimated independently of the latent quality of life parameters at the start of the treatment. Consequently, differential mortality, censoring mechanisms, and other mechanisms causing missing data can be ignored.