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Stapleton, Laura M.; Yang, Ji Seung; Hancock, Gregory R. – Journal of Educational and Behavioral Statistics, 2016
We present types of constructs, individual- and cluster-level, and their confirmatory factor analytic validation models when data are from individuals nested within clusters. When a construct is theoretically individual level, spurious construct-irrelevant dependency in the data may appear to signal cluster-level dependency; in such cases,…
Descriptors: Multivariate Analysis, Factor Analysis, Validity, Models
Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen – American Journal of Evaluation, 2016
Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…
Descriptors: Intervention, Multivariate Analysis, Mixed Methods Research, Models
von Davier, Matthias – ETS Research Report Series, 2007
This paper introduces multilevel extensions for the general diagnostic model (GDM) following recent developments on extensions of latent class analysis (LCA) to hierarchical models. The GDM is based on LCA as well as discrete latent trait models and may be viewed as a general modeling framework for conrmatory multidimensional item response models.…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Probability
Kariv, Dafna; Heiman, Tali – Journal of Adult and Continuing Education, 2005
The main objective of this study is to explore the coping behaviours of Israeli continuing education students who combine work and academic studies. Multi-level analyses revealed that: (1) perceived academic stress is determined by academic load and perceived work stress by workload; (2) coping strategies are related to an array of perceived…
Descriptors: Stress Variables, Stress Management, Coping, Hierarchical Linear Modeling