Extended latent class approach to the study of familial/sporadic forms of a disease: its application to the study of the heterogeneity of schizophrenia.

When no method exists for detecting genetic forms of a disorder, epidemiologists classify probands according to the presence or absence of an affected relative (familial or sporadic). Not only is this a surrogate measure but if the risk for the disorder is associated with characteristics such as age and gender, then probands with varied distributions of these characteristics among their relatives are subject to misclassification. A latent class approach is presented which explicitly models the relationship between the affected status of the relatives and the unobservable familial/sporadic status of the proband in order to adjust for these characteristics. Lastly, an approach is introduced to correct for attenuation in measures of association between familial/sporadic status and other variables that could result if probands are misclassified. This approach incorporates the latent class probabilities directly into the regression model without classifying probands. These methods are applied to a study of the heterogeneity of schizophrenia.