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The paper is devoted to the consequences of blind random selection of itemsfrom different item populations that might be based on completely uncorrelatedfactors for item inter-correlations and corresponding factor loadings. Based onthe model of essentially parallel measurements, we explore the consequences ofpresenting items from different populations across individuals and items fromidentical populations within each individual for the factor model and iteminter-correlations in the total population of individuals. Moreover, we explorethe consequences of presenting items from different as well as identical itempopulations across and within individuals. We show that correlations can besubstantial in the total population of individuals even when -- insubpopulations of individuals -- items are drawn from populations withuncorrelated factors. In order to address this challenge for the validity of ascale, we propose a method that helps to detect whether item inter-correlationsresult from different item populations in different subpopulations ofindividuals and evaluate the method by means of a simulation study. Based onthe analytical results and on results from a simulation study, we providerecommendations for the detection of subpopulations of individuals respondingto items from different item populations.

Heterogeneous item populations across individuals: Consequences for the factor model, item inter-correlations, and scale validity