Message-ID: <9e67c6e9ccf7463599f5660792022aef@maastrichtuniversity.nl>
Date: 2023-09-05T06:52:21Z
From: Wolfgang Viechtbauer
Subject: [R-meta] Checking for Multi-Collinearity with continuous and categorial predictors
In-Reply-To: <f1f4f68f1921492cab4b72e257dd7b89@mailbox.tu-dresden.de>
Dear Wilma,
In general, always provide a fully reproducible example to illustrate a problem. For example, like this:
library(metafor)
library(car)
dat <- dat.bangertdrowns2004
res <- rma(yi, vi, mods = ~ length + wic + feedback + info + pers + imag + meta, data=dat)
vif(res)
So the problem arises because you are loading the 'car' package *after* you have loaded metafor and it also has a vif() function. The vif() function from metafor is then 'masked', so calling vif() calls car::vif() and not metafor::vif(). But you can always explicitly tell R which vif() function to call, like this:
metafor::vif(res)
Best,
Wolfgang
>-----Original Message-----
>From: Wilma Charlott Theilig [mailto:wilma_charlott.theilig at mailbox.tu-
>dresden.de]
>Sent: Tuesday, 05 September, 2023 6:32
>To: Viechtbauer, Wolfgang (NP); R Special Interest Group for Meta-Analysis
>Subject: AW: Checking for Multi-Collinearity with continuous and categorial
>predictors
>
>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 at 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 at 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 at 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