You are here

Home › Forums › Third Party Software › metaSEM

Unable to run meta-SEM due to missing data

7 posts / 0 new
Log in or register to post comments
Last post
Mon, 04/22/2019 - 13:11
#1
smh1003's picture
smh1003
Offline
Joined: 04/22/2019 - 11:47
Unable to run meta-SEM due to missing data
AttachmentSize
Image icon Result of meta-SEM635.94 KB
Image icon Result of is.pd125.26 KB
Binary Data R-code for meta-SEM.R5.02 KB
File Arbour2010.csv96 bytes
File Ellis2009.csv115 bytes
File godin1986.csv96 bytes
File Haegele2017.csv86 bytes
File Kosma2007.csv113 bytes
File Kosma2009hr.csv96 bytes
File Kosma2009MET.csv95 bytes
File latimer2004paraintense.csv111 bytes
File latimer2004paramild.csv116 bytes
File latimer2004paramoderate.csv110 bytes
File latimer2004tetraintense.csv107 bytes
File latimer2004tetramild.csv107 bytes
File latimer2004tetramoderate.csv111 bytes
File latimer2005.csv115 bytes

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?

Top
Tue, 04/23/2019 - 08:49
Mike Cheung's picture
Mike Cheung
Offline
Joined: 10/08/2009 - 22:37
Could you please include the

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

Top
Tue, 04/23/2019 - 09:16
(Reply to #2)
smh1003's picture
smh1003
Offline
Joined: 04/22/2019 - 11:47
Dr. Chueng,

Dr. Chueng,

I uploaded R code and data set I used.

Top
Wed, 04/24/2019 - 00:02
Mike Cheung's picture
Mike Cheung
Offline
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)
Top
Wed, 04/24/2019 - 11:14
(Reply to #4)
smh1003's picture
smh1003
Offline
Joined: 04/22/2019 - 11:47
I really appreciate your

I really appreciate your quick and helpful answer!
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?

Top
Thu, 04/25/2019 - 08:55
Mike Cheung's picture
Mike Cheung
Offline
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.

Top
Sat, 05/04/2019 - 23:08
(Reply to #6)
smh1003's picture
smh1003
Offline
Joined: 04/22/2019 - 11:47
Dear Dr. Cheung,

Dear Dr. Cheung,

Sorry for late reply.
It worked well when I tried it again with your code.
I really appreciate your kind and helpful answer:)

Top

Copyright © 2007-2019 The OpenMx Project

Powered by Drupal