Summary
Contents
Subject index
Quantitative Psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods, and psychological measurement exist none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area.
Structural Equation Mixture Modeling
Structural Equation Mixture Modeling
Introduction
Applications of structural equation modeling (SEM) are often based on the assumption that the sampled data are identically and independently distributed (IID), according to the multivariate normal distribution. Letting yi denote the vector of observed variables of subject i, we express this as IID yi N(μ,Σ), where μ and Σ represent the population mean vector and covariance matrix, respectively. This expression implies that the population is homogeneous, in the sense that IID yi N(μ,Σ) should hold for every possible vector yi. Alternatively, if we view yi as the outcome of some (psychological) process, we may state that the observed vectors yi (i = 1,2,…,N) are independent outcomes of one and the same process, which gives rise ...
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