# Unable to run meta-SEM due to missing data

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Joined: 04/22/2019 - 11:47
Unable to run meta-SEM due to missing data
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First of all, I am grateful for asking my question to this forum where gurus of meta-SEM are helping people like me.
I am currently conducting meta-SME with the theory of planned behavior by following the example of Scalco17 in this website.
https://cran.r-project.org/web/packages/metaSEM/vignettes/Examples.html#scalco17
It seems my dataset work pretty well, but something is messing up the analysis.

Some data show 'NA' when I conducted the test for positive definite matrix using 'is.pd', and I think it is the reason for unreliable result because all results seems good when i conduct the analysis after eliminating data with NA from is.pd.

Would someone help me to figure this issue out?
How can I deal with missing data or NA from is.pd like this?

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Joined: 10/08/2009 - 22:37

Could you please include the data and R code so that we can replicate the errors?

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Joined: 04/22/2019 - 11:47
Dr. Chueng,

Dr. Chueng,

I uploaded R code and data set I used.

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Joined: 10/08/2009 - 22:37
The error is likely related

The error is likely related to the fact that two of the variances (Tau2_5 and Tau2_9) are near zero.

> VarCorr(mx.fit0)
Tau2_1       Tau2_2      Tau2_3      Tau2_4       Tau2_5      Tau2_6
Tau2_1  0.00680293 0.0000000000 0.000000000 0.000000000 0.000000e+00 0.000000000
Tau2_2  0.00000000 0.0006061789 0.000000000 0.000000000 0.000000e+00 0.000000000
Tau2_3  0.00000000 0.0000000000 0.009556938 0.000000000 0.000000e+00 0.000000000
Tau2_4  0.00000000 0.0000000000 0.000000000 0.003327514 0.000000e+00 0.000000000
Tau2_5  0.00000000 0.0000000000 0.000000000 0.000000000 1.847617e-11 0.000000000
Tau2_6  0.00000000 0.0000000000 0.000000000 0.000000000 0.000000e+00 0.006505271
Tau2_7  0.00000000 0.0000000000 0.000000000 0.000000000 0.000000e+00 0.000000000
Tau2_8  0.00000000 0.0000000000 0.000000000 0.000000000 0.000000e+00 0.000000000
Tau2_9  0.00000000 0.0000000000 0.000000000 0.000000000 0.000000e+00 0.000000000
Tau2_10 0.00000000 0.0000000000 0.000000000 0.000000000 0.000000e+00 0.000000000
Tau2_7     Tau2_8       Tau2_9    Tau2_10
Tau2_1  0.000000000 0.00000000 0.000000e+00 0.00000000
Tau2_2  0.000000000 0.00000000 0.000000e+00 0.00000000
Tau2_3  0.000000000 0.00000000 0.000000e+00 0.00000000
Tau2_4  0.000000000 0.00000000 0.000000e+00 0.00000000
Tau2_5  0.000000000 0.00000000 0.000000e+00 0.00000000
Tau2_6  0.000000000 0.00000000 0.000000e+00 0.00000000
Tau2_7  0.001114616 0.00000000 0.000000e+00 0.00000000
Tau2_8  0.000000000 0.01365853 0.000000e+00 0.00000000
Tau2_9  0.000000000 0.00000000 1.223589e-20 0.00000000
Tau2_10 0.000000000 0.00000000 0.000000e+00 0.03870517

Rerunning the model seems to work.

mx.fit0 <- rerun(mx.fit0, extraTries=50)
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Joined: 04/22/2019 - 11:47
I really appreciate your

So, in this case, should I report the result as is?
Since the summary of mx.fit0 shows below message,
** Information matrix is not positive definite (not at a candidate optimum),
does it mean the overall fit of the model is not trustworthy and the result of meta-analysis is not credible?

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Joined: 10/08/2009 - 22:37
Does rerunning the model work

Does rerunning the model work? It worked fine in my R.

If it still does not work, you may increase the number of trials, e.g., 100, and see if it works better.

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Joined: 04/22/2019 - 11:47
Dear Dr. Cheung,

Dear Dr. Cheung,