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The article Beyond SEM: General Latent Variable Modeling, written by Bengt. O. Muthen.

Selectivity problems can occur whenever one tries to estimate population parameters from a nonrandom sample. The sample may be nonrandom because only individuals with certain characteristics are selected into the sample (sample selection), or because individuals participate voluntarily in the sample (self-selection). Selective samples can also occur because individuals fall out of the sample for various reasons, despite an initial random sample (attrition). In such situations it is important to model the selection process as realistically as possible. Selectivity problems are discussed in terms of a general model that is estimated by the maximum likelihood method. Both single-group and multiple- group analyses are considered. The multiple-group case is related to the problem of evaluation of treatment effects in nonequivalent control group designs. The general model and the estimation procedure is illustrated by means of a simulation study. An extension of the general model to latent variable models is discussed.