Developmental aspects of psychiatric disorders may be inferred from patterns of age differences in prevalence. Age-specific prevalences are provided for nine disorders in a general population sample of ages 10-20. Age and gender patterns for several disorders suggest developmental stage-associated risks. These include oppositional disorder in both genders and conduct disorder and major depression in girls. Major depression shows a pattern suggestive of a role for the onset of puberty. The prevalence of one or more disorders did not differ by age or gender. However, the pattern of specific diagnoses varied greatly by both age and gender.
Some problems in the measurement of latent variables in structural equations causal models are presented, with examples from recent empirical studies. Latent variables that are theoretically the source of correlation among the empirical indicators are differentiated from unmeasured variables that are related to the empirical indicators for other reasons. It is pointed out that these should also be represented by different analytical models, and that much published research has treated this distinction as if it had no analytic consequences. The connection between this theoretical distinction and disattenuation effects in latent variable models is shown, and problems with these estimates are discussed. Finally, recommendations are made for decisions about whether and how to measure latent variables when manifest variables are potentially available. Index terms: causal models, disattenuation, emergent variables, latent variable measurement, latent variables, structural equations modeling.
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