I am attempting to fit a model to my data for meta-analysis I'm working on. The response is binary (0 or 1), and I want to specify a binomial distribution with logit link function. The 2-3 (depending on the model) explanatory variables are all categorical.
rma.glmm, but this doesn't appear to support the use case when you already have a single response variable column, but instead supports a number of cases that don't fit this one (e.g, 2 x 2 contingency tables, etc.). I do have weights for the model as well. The weights are based on sample sizes.
The first six rows of the data look like this:
subject type weight response 1 c abiotic 12.0 0 2 c temporal 18.0 1 3 p temporal 40.0 0 4 p temporal 4.0 0 5 m spatial 105.5 1 6 c temporal 70.0 1
response is the response variable,
weight is the weight, and
type are two categorical moderator variables.
metafor actually support my use case, or any other R packages (e.g.,