How to address too many missing

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No user picture. Xin Lin Joined: 06/10/2019
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Dear Dr. Cheung and colleagues,

We are trying to investigate the predictors of an outcome using longitudinal studies. Yet, there are some studies with only one or two predictors.

Is there an algorithm that allows us to handle missing correlation or remove those correlation matrices containing only one correlation coefficients?

Thanks for your time and patience.

Replied on Wed, 09/02/2020 - 06:30
Picture of user. Mike Cheung Joined: 10/08/2009

Dear Xin Lin,

If you want to drop studies with many missing values, you may use is.na() to check whether there are missing values and drop them using standard R functions.

Best,
Mike

Replied on Wed, 09/02/2020 - 11:24
No user picture. Xin Lin Joined: 06/10/2019

In reply to by Mike Cheung

Dear Mike,

Thank you for your reply.
Are there any citations support the removal of correlation matrices containing too much NA in MASEM?

Best,
Xin

Replied on Fri, 09/04/2020 - 00:07
Picture of user. Mike Cheung Joined: 10/08/2009

Dear Xin,

No, I don't think so.

Personally, I will try to keep as many data as possible.

Best,
Mike