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| Shau, Wen-Yi | 1 |
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Martens, Matthew P. – Counseling Psychologist, 2005
The four reactions in the May 2005 issue of "The Counseling Psychologist" address several considerations regarding the use of structural equation modeling (SEM) in counseling psychology research, including its appropriateness for analyzing one's data and testing one versus multiple theoretical models. In addition, points that are not mentioned in…
Descriptors: Models, Counseling Psychology, Structural Equation Models, Item Analysis
Marsh, Herbert W.; Wen, Zhonglin; Hau, Kit-Tai – Psychological Methods, 2004
Interactions between (multiple indicator) latent variables are rarely used because of implementation complexity and competing strategies. Based on 4 simulation studies, the traditional constrained approach performed more poorly than did 3 new approaches-unconstrained, generalized appended product indicator, and quasi-maximum-likelihood (QML). The…
Descriptors: Structural Equation Models, Item Analysis, Error Patterns, Computation
Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang – Structural Equation Modeling: A Multidisciplinary Journal, 2006
This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…
Descriptors: Structural Equation Models, Path Analysis, Simulation, Equations (Mathematics)
Bowles, Tyler J.; Jones, Jason – Journal of College Student Retention: Research, Theory & Practice, 2004
Single equation regression models have been used rather extensively to test the effectiveness of Supplemental Instruction (SI). This approach, however, fails to account for the possibility that SI attendance and the outcome of SI attendance are jointly determined endogenous variables. Moreover, the standard approach fails to account for the fact…
Descriptors: Academic Ability, Supplementary Education, Instructional Effectiveness, Regression (Statistics)

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