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- W1978048735 abstract "Two-level data sets are frequently encountered in social and behavioral science research. They arise when observations are drawn from a known hierarchical structure, such as when individuals are randomly drawn from groups that are randomly drawn from a target population. Although 2-level data analysis in the context of structural equation modeling can be conducted by easily accessible software such as LISREL, the group- and individual-level effects are usually treated as though they are uncorrelated. When extra group variables are measured and their relationships with individual-level variables are studied, the analysis of cross-level covariance structures is of interest. In this article, we propose a model setup framework in Mx that allows the analysis of cross-level covariance structures. An illustrative example is given and a small-scale simulation study is conducted to examine the performance of the proposed procedure. The results show that the proposed method can produce reliable parameter and standa..." @default.
- W1978048735 created "2016-06-24" @default.
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- W1978048735 date "2009-01-20" @default.
- W1978048735 modified "2023-09-24" @default.
- W1978048735 title "Using Mx to Analyze Cross-Level Effects in Two-Level Structural Equation Models" @default.
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- W1978048735 doi "https://doi.org/10.1080/10705510802561527" @default.
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