[R-meta] Checking for Multi-Collinearity with continuous and categorial predictors

[Wilma Charlott Theilig]

Dear Wolfgang,

first of all, thank you for your reply!

If I follow your description, I get the following error:


Error in x$terms %||% attr(x, "terms") %||% stop("no terms component nor attribute") :

  no terms component nor attribute

In addition: Warning message:

In vif.default(res2) : No intercept: vifs may not be sensible.


Is there a way to fix this?

I would really appreciate your help!

Thank you so much in advance.


Best,

Wilma





________________________________
Von: Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer using maastrichtuniversity.nl>
Gesendet: Samstag, 2. September 2023 13:16:07
An: R Special Interest Group for Meta-Analysis
Cc: Theilig, Wilma Charlott
Betreff: RE: Checking for Multi-Collinearity with continuous and categorial predictors

Dear Wilma,

You mean in a meta-regression analysis? You can do this with metafor::vif(). After fitting a meta-regression model, you can use the vif() function to obtain variance inflation factors to indicate the degree of multicollinearity of the predictors. The predictors can be both continuous and categorical, so this works just fine.

See here for the documentation (and examples):

https://wviechtb.github.io/metafor/reference/vif.html

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>Behalf Of Wilma Charlott Theilig via R-sig-meta-analysis
>Sent: Saturday, 02 September, 2023 11:29
>To: r-sig-meta-analysis using r-project.org
>Cc: Wilma Charlott Theilig
>Subject: [R-meta] Checking for Multi-Collinearity with continuous and categorial
>predictors
>
>Hi all,
>
>I wanted to ask if it is possible to check both continuous and categorical
>predictors for multi-collinearity at the same time (in one analysis, so to speak)
>and how I can implement this in R.
>
>If anyone can help me in this regard, I would be very pleased!
>
>Kind regards
>
>Wilma

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