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Paul Silvia posted on Tuesday, February 17, 2009 - 12:18 am
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Hi: I've been reading Cheung's work on meta-analytic SEM, which pools correlation matrices via multiple-group analysis. Will Mplus output such a pooled matrix, given summary correlation data? (To tinker, I used summary data in correlation matrix form for 3 groups (same variables, no missing data) using NGROUPS and NOBSERVATIONS. The SAMPSTAT and TECH1-4 output reports separately for each group, but not for the combined sample.) Thanks, Paul |
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I can't think of any way to do this in Mplus. I'm assuming the pooled correlation matrix is the average of the three correlation matrices. |
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Paul Silvia posted on Tuesday, February 17, 2009 - 3:43 pm
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Yup, it's just the average of the matrices. It sounds like it's time for the old-school approach: pen, paper, and calculator. Paul |
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Mike Cheung posted on Saturday, March 28, 2009 - 8:48 am
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Hi Paul, Mplus can be used to pool correlation matrices. The following is the sample Mplus code: TITLE: Pooling correlation matrices DATA: FILE = test.cov; NGROUPS=2; TYPE IS COVARIANCE; ! Pretend correlation matrices as covariance matrices ! See Cheung and Chan (2005) NOBSERVATIONS = 100 100; VARIABLE: NAMES ARE x1-x3; USEVAR ARE ALL; MODEL: latent1 BY x1*; ! Estimated standard deviations latent2 BY x2*; latent3 BY x3*; latent1@1; latent2@1; latent3@1; x1@0; ! No measurement errors x2@0; x3@0; latent1 WITH latent2* (1); latent1 WITH latent3* (2); latent2 WITH latent3* (3); MODEL g2: latent1 BY x1*; ! Estimated standard deviations latent2 BY x2*; latent3 BY x3*; latent1 WITH latent2* (1); ! Constrain correlation matrices latent1 WITH latent3* (2); latent2 WITH latent3* (3); OUTPUT: SAMPSTAT; Regards, Mike |
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Hi.... I have also been reading Cheung's work on meta-analytic SEM. Might I ask if I can use the raw data to "create" a pooled correlation matrices or covariance matrices? And if I have obtained a pooled correlation matrices or covariance matrices in Mplus, how I can use it to do a CFA? Thank you very much for your kind attention. Kit |
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See the SAMPLE option in SAVEDATA. You can use this to create a pooled-within covariance matrix. See Example 13.1 for how to use a covariance matrix as data. For a pooled-within covariance matrix the sample size is the number of observations minus the number of clusters. |
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Thank you very much for your reply. |
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Dear Drs. Muthen & Muthen, I am performing a meta-analytic SEM on a pooled correlation matrix with many missing cells. Is Mplus capable of taking in summary data (such as FULLCORR) with missing cells at all? Here's my input code: DATA: FILE = MASEM2.csv; TYPE IS FULLCORR; NOBSERVATIONS = 45925; VARIABLE: NAMES ARE AGE1-AGE26; USEVARIABLES ARE AGE1-AGE26; ANALYSIS: TYPE = GENERAL; ESTIMATOR=ML; If Mplus is not designed to handle summary data with missing cells, what would you recommend I do to handle the missing cells? Impute them with another software? If so, is there a software that you would recommend? Thank you very much! Best regards, Ke Anne Zhang |
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No, Mplus cannot handle summary data with missing cells. I don't know of a program that can. |
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ehrbc1 posted on Wednesday, March 23, 2016 - 11:57 pm
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Hello, I have tested the same path analytic model across a number of studies, and now the next obvious step is to run a MASEM. I’m interested in the significance of individual direct pathways, indirect effects and total effects. Across my studies, I have also tested the relative magnitude of these various paths (using the model constraint option in MPLUS). So I would be interested in examining these relative magnitudes based on the pooled correlation matrix, but I understand that MPLUS can’t handle Cheung’s TSSEM and the WLS estimation method? Any suggestions as to how I can conduct this analysis in MPLUS? Thank you. |
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You can do meta analysis as shown in our Topic 9 handout (last version) on slide 150 and on. |
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