Dear Bernd,
Please be careful in reading the example of meta-regression (12.4) in
http://cran.r-project.org/doc/vignettes/HSAUR/Ch_meta_analysis.pdf.
In that example, the variance component was estimated under a model
without any covariate. Then the estimated variance component was used
as the
Dear Donglei Hu,
If you have two correlation coefficients, you may try cordif {multilevel}
and cordif.dep {multilevel} for the independent correlations and for the
dependent correlations, respectively. However, they are both based on the
sampling distribution of correlation coeficient. A better
Dear all,
Edmond Ng (http://multilevel.ioe.ac.uk/softrev/reviewsplus.pdf) provides
an example to fit the mixed effects meta-analysis in Splus 6.2. The
syntax is:
lme(fixed=d~wks, data=meta, random=~1|study, weights=varFixed(~Vofd),
control=lmeControl(sigma=1))
where d is the effect size, study
Dear List,
I have some discrete data and want to calculate the percentiles and the
percentile ranks for each of the unique scores. I can calculate the
percentiles with quantile().
I know that ecdf can be used to calculate the empirical cumulative
distribution. However, I don't know how to
