For example ,

I would like to integrate all significant variables into one model to see if tau index is significantly decreased.

But I realized that , from the example from Cheung;

" http://courses.nus.edu.sg/course/psycwlm/internet/metaSEM/index.html"

I would like to put all predictors "Year, Discpline, Country.." into one model as final.

I realized that 'cbind()' function is limited to variable like "Discipline".

If i try to add "Year" to the equation, a error message appears.

> summary(Model5 <- meta3(y=fisherz, v=v, cluster=id, x=cbind(weeks, timepoint,(")dissertation("),(")peerreview(")), data=KORdb, intercept.constraints=0, model.name="Model5"))

Weeks, timepoint are continuous whereas dissertation and peerreview are processed as dicotomous.

How can i integrate variables with different characteristics into one model??