Third Party Software

Hello all,

I am trying to conduct a parameter based MetaSEM. My model includes several mediators which are in parallel, and one mediator in series with the others (Attached is the figure summarising the model).

I have tried to run the code, however, R is giving me the following error message:
Error in (function (x, n, standardized = TRUE, direct.effect = TRUE, run = TRUE) : length of 'dimnames' [1] not equal to array extent
Error: object 'indirect1' not found

I have attached the code I am currently using.

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,
I am a beginner to both SEM and Onyx..., but see both as highly useful for my research field, plant ecology.

Playing around with a model including many variables, i find that i have to reapply model customization over and again when i compare models with the clone and drag-compare method.

Would it be possible to let clones inherit the customization of the parent ? (path style, show/hide variances etc.)

Many greetings and thanks for a wonderful software !

Thure

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!