[R-meta] Meta-analysis for agronomical data

Norman DAURELLE norm@n@d@ure||e @end|ng |rom @grop@r|@tech@|r
Wed May 13 01:11:29 CEST 2020

Hello,I would like to use a meta-analysis method to summarize the scientific literature that has been published about the relationship between a plant disease (Blackleg, caused by the fungus Leptosphaeria maculans) and oil rapeseed yield.I have read about meta-analyses and I tried using a meta-analysis method, the one explained by Daniel Quintana in the paper " From pre-registration to publication : a non-technical primer for conducting a meta-analysis to synthesize correlational data" and the youtube video that relates to it, but the object of my interest is more the estimated slope of the regression between disease level and yield than the correlation. Also, the escalc function of the Metafor package requires at least 4 "replications" (or I don't know exactly what to call it, but it is a number of individuals for the sample size of each study in medical sciences) for each effect-size, each study, and in my data what comes closest to a number of individuals would be the number of replications made for each (fungicide or other) treatment, which is sometimes smaller than 4.to be more explicit I used this line of code :data <- escalc(measure="ZCOR", ri=r, ni=number_of_rep, data=data, slab=paste(author, year, sep=", ")) and I get this error message :
Warning message:
In escalc(measure = "ZCOR", ri = r, ni = number_of_rep, data = data,  :
  Cannot estimate the sampling variance when ni <= 4.I multiplied my "number_of_rep" by 10 to see what results the analysis would give, but I am not confident in the fact that this is a rigorous thing to do.Furthermore I have only seven studies, and from what I read in the plant pathology literature, it seems like a pretty small number of studies. As a comparison, in a paper published in 2009 by Madden et al. (Meta-Analysis for Evidence Synthesis in Plant Pathology : An Overview), they used 101 studies for their meta-analysis... So that made me think maybe there was altogether not enough data for me to use in my meta-analysis, but I would really like to make sure that I have tried everything I could to make it work.Do you have any advice regarding what package and what function to use that would be suitable for a dataset including only 7 studies, and which doesn't have the exact equivalent for the number of individuals that make up the sample sizes ?I would be really grateful.Thank you !Norman
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