Problems using `r2_nakagawa()`

[Franelizabethgalvez]

I have been evaluating the quality of modelfit with the easystats package (0.7.1.2). Since I have mixed models I use the r2_nakagawa() function and since the last update I did (easystats::install_latest(force = TRUE)) this function gives me strange values.

For example for this model: m2<-glmmTMB(FvFm ~ hora*temperatura + (1|Experimento), data=d, family=beta_family(link="logit"))

I used to get these values: r2_nakagawa(m2) # R2 for Mixed Models Conditional R2: 1.000 Marginal R2: 0.973

and now it gives me these values:

# R2 for Mixed Models Conditional R2: 1.341 Marginal R2: 1.306

I don't know what's wrong, but I have the latest version of easystats and performance and insight.

Someone is having these problems, I think it is not code. any help is welcome and appreciated!!

[strengejacke]

This issue is probably fixed in https://github.com/easystats/insight/pull/883. Do you have a reproducible example?

[strengejacke]

Closing this, as it should be fixed in insight and performance meanwhile.

[Franelizabethgalvez]

Thanks for the help, I know this question was closed, but I leave this link https://stackoverflow.com/questions/78557157/strange-values-for-r2-nakagawa-with-easystats/78667344#78667344.

I also leave my reproducible example: first I did this: install.packages("insight", repos = "https://easystats.r-universe.dev") install.packages("performance", repos = "https://easystats.r-universe.dev")

then I restarted R. I ran my model: d<-read.delim("ice20Chloromi6M_5exp_2.txt", header=T) m2<-glmmTMB(FvFm ~hora*temperatura + (1|Experimento),data=d, family=beta_family(link="logit"))

and I got these new values for r2_nakagawa(m2)

Conditional R2: 0.990 Marginal R2: 0.963

I hope you get the same values!! ice20Chloromi6M_5exp_2.txt