The factor analysis of repeated measures psychiatric data presents interesting challenges for researchers in terms of identifying the latent structure of an assessment instrument. Specifically, repeated measures contain both within and between individual sources of variance. Although a number of techniques exist for separating out these 2 sources of variance, all are problematic. Recently, researchers have proposed that exploratory multilevel factor analysis (MFA) be used to appropriately analyze the latent structure of repeated measures data. The chief objective of this report is to provide a didactic step-by-step guide on how MFA may be applied to psychiatric data. In the discussion, we describe difficulties associated with MFA and consider challenges in factor analyzing life event appraisals in psychiatric samples.
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