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Dear all, I am developing a generalized linear mixed model for my meta-analysis on lameness prevalence in British Dairy Cattle. Everything seems to be working fine however when I try to identify outlier using functions rstudent, leave1out and influence...

Dear all, I am conducting a meta-analysis on a binomial variable. I used the following code *> pes.glmm=rma.glmm(xi=nlameanimal, ni=ssizeanimal, data=prevalence_2020_nomv, measure="PLO")* *> pes=predict(pes.glmm, transf=transf.ilogit)> print(pes...

Dear all, I am running a meta-analysis on the prevalence of lameness (binary) in British dairy cattle and have used the *metaprop* from the *metafor* package. I have set the model to run with random effects, using the DL...

You are absolutely right Guido. I am sorry for another mistake. Attached the new cvs file with all the needed information. I am totally lost as to why R is providing such results so I would again me extremely grateful...

Dear all, I am sorry to come to you once again with my questions about the meta-analysis results. I thank all the help provided so far but sadly it seems that can't get robust result. I will try...

Dear all, I am conducting a meta-analysis and came across an odd issue. I ran the model for assessing the moderator effect of a variable as per below *subganal.lcmbi=rma(yi, vi, data=ies.logit.lcmbi, mods=~lcmbi...

Dear all, I am conducting a meta-analysis on incidence data. I have basically adapted a previous model that I had used for conducting an analysis on prevalence data, producing the following model: *ies.da=escalc(xi=nototal_stand, ti...

Dear all, I think I have managed to set the model for running the meta-analysis using metaprop function and run the outlier and influential case diagnostic using the InfluenceAnalysis function. I have a question regarding the output of my...

Dear all, I am conducting a meta-analysis and came across an odd issue. I ran the model for assessing the moderator effect of a variable as per below. *subganal.lcmbi=rma(yi, vi, data=ies.logit.lcmbi, mods=~lcmbi...

Dear Gerta, That seems to be again a error from my side as I forgot to provide the code for the double arcsine transformation of the data. Once again I apologise for all these mistakes (I admit I am new...

Dear all, I am conducting a meta-analysis on prevalence and incidence data. As there is plenty of heterogeneity I am doing a sub-group analysis. However I am finding the output of the same and forest plots produced to...

Dear all, Sorry for the double posting and previous "messy" message. I am conducting a meta-analysis on prevalence and incidence data. As there is plenty of heterogeneity I am doing a sub-group analysis. However I am finding the...

Dear all, Once again I am sorry for posting this message again but I forgot to send the outputs. Again I am conducting a meta-analysis on prevalence and incidence data. As there is plenty of heterogeneity I am doing...

Dear all, I hope you all had a great weekend. I have been sending some questions to the r-project because of my meta-analysis on prevalence data. Recently I can across a paper calling attention to the eventual misleading...

Dear Michael, Thank you for your prompt reply. Sorry for my eventual mistake with the *metaprop *command. It is likely that it comes from the *meta* package. I had to install it as well as the *metafor* package, to run...

Dear Gerta, Thank you so much for all the insights and guidance. I was looking at the figures and there is still one thing I can't make sense of which relates to this part of the code: > print(pes...

Dear Guido, Thank you so much for your reply and help. I can see that your forest plot results differ only in the estimates for each group (as a result of assuming a common or different tau2 values). I also...