I am looking to conduct a meta-analysis in R using {netmeta}. However, my outcome of interest is a little bit complex and would appreciate advice in how best to enter it into the dataset.
I am looking at the cleavage rate of oocytes for in vitro fertilisation following nutritional supplementation in cattle. Most of the studies do not state a mean +/- s.e.m. or s.d. in their results – they mainly report it as a proportion.
As cleavage is technically a binary outcome (has it cleaved? Yes or no?) I was going to convert the proportions to a risk ratio (which is fairly straightforward). However, one of the issues is that most of the studies collect oocytes on more than one occasion from the animals in the experiment. For example, they may have five animals in the control group and five animals in the experimental group, which undergo three oocyte collection cycles. However, the results of the three collections are just averaged for most studies, e.g. an average of 6/11 oocytes cleaved (54.5%) over the three collections and five animals in the control group and 9/15 (60%) in the experimental group. I feel like I need to account for the sample size of each study but just inputting 6 and 11, and 9 and 15 in the below columns:

doesn’t account for this.

Is it appropriate to just multiply the number of animals by the number of collections to estimate the total events and total numbers, or is that seriously oversimplifying it and potentially introducing sampling error?