Suppose I have this type of data in meta-analysis (example):
I want to calculate RR of plants abundance as the log-transformed ratio of treatment/control. Assuming it is ok for my study to remove observation that have 0 values in the control, you still get infinite estimates in the observations that have 0 values in the control when using log-transformed ratios.
Is any of the two following option accepted in meta-analysis?
1) Make a continuity correction of +1 in both treatment and control to avoid this issue. However, I have data measuring the change in plant abundance but with different units (i.e. % of cover, biomass, number of shoots) which in the end makes the data out of proportion with values in some observations extremely higher/lower compared to others. Isn't a problem to add the same +1 factor in each observation in my case? Shouldn't you apply a continuity correction factor in proportion to the values reported to account for these differences?
2) (best option to me so far) I can just avoid to log-transform the response ratio so to have an effect size = 0 in case of 0 values in the treatment and exclude observations with 0 values in the control. However to not logtransform the response ratios is really not ok in meta-analysis apparently...