[R-meta] R Bayesian Meta-regression, how to test covariates?

[Mark Pilling]

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I'm using the bmeta package in R to conduct a Bayesian Meta-regression.The function allows covariates to be entered by including them as "X" variables in a data.list object.

My question (possibly stupid), is where are the regression covariates in the output?

Data from p12 of bmeta_manual.pdf, with a made-up covariate added:
Study   study   year    y   var prec    Covar_bin
1   Hwang   2004    1.3 3.0888167   0.3237486   0
2   Ashrafi 2005    -4.79   4.2111455   0.2374651   0
3   Ensieh  2010    -2.49   3.0201244   0.3311122   0
4   Agha    2010    -3.39   1.5519691   0.6443427   1
5   Kim 2012    -0.5    0.6469829   1.5456359   1
6   Bulent  2012    -1  1.6380733   0.6104733   1
Reproducible example

data<-read.csv("Book1.csv")

Meta-analysis
data.list1<-list(y=data$y, prec = data$prec)
x1<-bmeta(data=data.list1, outcome ="ctns", model="std.mv", type="ran")

x1

mu=-1.613

Meta-regression
data.list2<-list(y=data$y, prec = data$prec, X=cbind(data$Covar_bin))
x2<-bmeta(data=data.list2, outcome ="ctns", model="reg.mv", type="ran")

x2

mu=-1.717

So the overall effect estimate (mu) has changed, but why is there no output for the regression covariate to determine if it should be included?
 

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