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http://hdl.handle.net/2152/1496
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| Title: | Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data [electronic resource] |
| Authors: | Furlow, Carolyn Florence.
Beretvas, S. Natasha |
| Keywords: | Education, Educational Psychology. |
| Issue Date: | 27-Jan-2006 |
| Publisher: | The University of Texas at Austin |
| Abstract: | This study compared the effects of different methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under various patterns of missingness on the estimation of correlation parameters and the resulting SEM parameters and fit indices. Univariate weighting methods for synthesizing correlations are frequently used. An alternative multivariate method for pooling correlation matrices involves using generalized least squares (GLS), where the dependencies of the correlations within the same matrix are taken into consideration (Becker, 1992). Since previous research has reported poor performance with GLS versus univariate weighting procedures, a revised GLS method, W-COV GLS, was used. Both the W-COV GLS procedure and univariate weighting were compared using correlations transformed with Fisher's z versus untransformed correlations. |
| URI: | http://hdl.handle.net/2152/1496 |
| Appears in Collections: | Theses and Dissertations from The University of Texas at Austin
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