metaSEM

Dear Mike,

I'm afraid I have to ask you for help again.
I receive a following new error warning every time I try to run an FEM regardless of the constellation of variables from my dataset:
> summary(fixed1)
Error in if (pchisq(chi.squared, df = df, ncp = 0) >= upper) { :
missing value where TRUE/FALSE needed
Even if I try to run it only with first three variables (there are 146 full matrices without any missings) I have the same problem.
I appreciate any idea you can provide.

Regards,
Nastja

Dear all,

Being very new to MetaSEM as well as R, please accept my apology for such simple question.

Mike kindly corrected my code to conduct a correlation based MetaSEM.

I just wanted to be sure that the coefficients are the standardised coefficients. Also, I was wondering whether it is possible to get the CI of the indirect effects, to know whether these effects are significant or not.
I attached the code and the results.

Thank you in advance,
Regards,
Arin

Dear Mike,

I'm a beginner in R and metaSEM. I'm performing a meta-analytic path model with 3 predictor variables, 1 mediator and 1 dependent variable (5 variables in total and 158 primary studies) as you can see in the figure.

I run the fix effects in the full dataset (158) but it is not possible because the missing values, but neither is possible to run the random effects (1stage).

Hi Mike and others,

I've been running some three-level meta-analyses using meta3() with standard error as input instead of variance. However, the description of meta() and meta3() only mention the use of variance as input. Although I am aware it is easy to convert standard error to variance I was wondering whether it is ok to use standard error with meta() and meta3().

Thanks for the help all.

Best,
Jasper

Hi Mike, and others,

A fixed effect model is a more restricted version of a random effects model, when meta-analyzing correlations using tssem1(), correct? Is there a way to do a nested model test? I know the degrees of freedom for the difference test would be the number of random effects estimated. I'm tripped up because the fixed effect model gives many fit stats, whereas the random effects model only gives a -2 log likelihood.

Thank you!

Hi Mike and other users,

I have a question concerning the the function asycov in the preparatory process for a Meta-Analysis using SEM and the WLS-Function. I have a manually created pooled correlation matrix (6x6) as there are some correlations I didn’t compute by myself. The problem is, that there are 4 missing values which resulted in the following error term when trying to calculate the covariance matrix with the asycov function:

Hi Mike and metaSEM users,

First of all, thank you, Mike, for maintaining such an active presence on this forum! It makes a HUGE difference as a user to be able to get questions answered from the package maintainer within a pretty reasonable timeframe. :)

I had another question about the meta-analytic indirect effects that are estimated by indirectEffect() (and then meta-analytically combined using meta() ).

Hi All,

I need to calculate variance explained for my endogenous latent variables after fitting the pooled data to a structural model in Stage 2 (using tssem2). I have specified a model (all observed variables) with 3 dependent variables (two of which are mediators, with one key "final" dependent variable).

(I guess I'll drop in the A matrix so you know what it looks like:)

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