The paper is devoted to the consequences of blind random selection of items from different item populations that might be based on completely uncorrelated factors for item inter-correlations and corresponding factor loadings. Based on the model of essentially parallel measurements, we explore the consequences of presenting items from different populations across individuals and items from identical populations within each individual for the factor model and item inter-correlations in the total population of individuals. Moreover, we explore the consequences of presenting items from different as well as identical item populations across and within individuals. We show that correlations can be substantial in the total population of individuals even when -- in subpopulations of individuals -- items are drawn from populations with uncorrelated factors. In order to address this challenge for the validity of a scale, we propose a method that helps to detect whether item inter-correlations result from different item populations in different subpopulations of individuals and evaluate the method by means of a simulation study. Based on the analytical results and on results from a simulation study, we provide recommendations for the detection of subpopulations of individuals responding to items from different item populations.

翻译：本文专门论述从不同物品群体中盲目随机选择物品的后果,这些物品可能基于物项相互关系和相应要素负荷的完全不相关因素。根据基本上平行的测量模式,我们探讨将不同人口群体中的物品在各个人和同一人口群体中的物品提交要素模型和项目在个人总人口中的相互关系的后果。此外,我们探讨在个人之间和个人内部展示不同和相同项目群体中的物品的后果。我们表明,在个人总人口中,即使 -- -- 在个人亚群体中 -- -- 从非相关因素群体中提取的物品 -- -- 也可能具有实质性关联性。为了应对规模有效性的这一挑战,我们建议一种方法,帮助检测项目之间是否因不同项目群体在个人不同亚群体中产生关联,并通过模拟研究评估方法。我们根据分析结果和模拟研究的结果,为检测不同项目群体中个人对物项作出反应的子群提供了建议。