Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data [electronic resource]
| Title: | Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data [electronic resource] |
| Author: | Furlow, Carolyn Florence. |
| 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
http : / /hdl .handle .net /2152 /1496 |
| Date: | 2006-01-27 |
Citation
(2003).
Meta-analytic methods of pooling correlation matrices for structural equation modeling under different patterns of missing data [electronic resource].
Doctoral dissertation,
The University of Texas at Austin. Available electronically from
http : / /hdl .handle .net /2152 /1496
.
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