uniR2 | R Documentation |
It conducts the second stage analysis of the uniR analysis by fitting structural equation models on the average correlation matrix.
uniR2mx(x, RAM = NULL, Amatrix = NULL, Smatrix = NULL, Fmatrix = NULL,
model.name=NULL, suppressWarnings=TRUE, silent=TRUE,
run=TRUE, ...)
uniR2lavaan(x, model, ...)
x |
An object of class |
RAM |
A RAM object including a list of matrices of the model
returned from |
Amatrix |
If |
Smatrix |
If |
Fmatrix |
If |
model.name |
A string for the model name in
|
suppressWarnings |
Logical. If |
silent |
Logical. An argument to be passed to |
run |
Logical. If |
model |
A model specified using lavaan syntax see |
... |
Further arguments to be passed to either
|
This function implements the univariate r approach proposed by Viswesvaran and Ones (1995) to conduct meta-analytic structural equation modeling (MASEM). It treats the average correlation matrix as if it was a covariance matrix in fitting structural equation models. The harmonic mean of the sample sizes in combining correlation coefficients is used as the sample size in fitting structural equation models. It is included in this package for research interests. The two-stage structural equation modeling (TSSEM) approach is preferred (e.g., Cheung, 2015; Cheung & Chan, 2005).
A fitted object returned from mxRun
or sem
.
Mike W.-L. Cheung <mikewlcheung@nus.edu.sg>
Cheung, M. W.-L. (2015). Meta-analysis: A structural equation modeling approach. Chichester, West Sussex: John Wiley & Sons, Inc.
Cheung, M. W.-L., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach. Psychological Methods, 10, 40-64.
Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psychometric meta-analysis and structural equations modeling. Personnel Psychology, 48, 865-885.
uniR1
, lavaan2RAM
,
Becker09
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