Length-of-stay data of the type used as criteria for assessing various kinds of treatment programs poses a number of data analysis problems due to Ss becoming lost to follow-up, unresponsive Ss being withdrawn at the end of the study, Ss entering the study sequentially, and observations being arbitrarily truncated at some time point for purposes of analysis. Such data are often described as data containing ‘censored’ observations. Techniques for handling such data have been worked out extensively in industrial and human survival studies but are not commonly available in quantitative psychology literature. Adaptations of such methods are suggested for assessing the results of treatment programs associated with alcoholism problems, the rehabilitation of blind veterans, recidivism among neuropsychiatric patients, and the treatment of epileptic patients. The paper focuses on 5 classes of analytic procedures: actuarial, nonparametric, stochastic-Markov, randomization, and maximum likelihood regression, and discusses such procedures with respect to assumptions, sample-size requirements, characteristics of the censored observations, types of test statistics, ability to consider ancillary variables, and ease of computation.
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