Ecological meta-analyses often encounter incompletely reported studies that have missing variance measures (e.g. standard deviations, SDs) or sample sizes (SSs) that are necessary for incorporating the study in a weighted meta-analysis. Here, we evaluated 14 different options to treat missing information in simulated data sets of known structures and between 10% and 90% of missing standard deviations and/or sample sizes.
Script 1 (Mainscript)
- creates meta-analysis data sets (group comparisons and correlation analyses) with varying size, range of SD and SS values and correlation structures
- deletes between 10 and 90% of SDs and/or SSs completely at random (MCAR), at random (MAR) or not at random (MNAR)
- applies 14 approaches to treat/impute those deleted values
- saves the obtained grand mean estimates in a folder that must be named "intermediate output"
Script 2(additional functions2 - bias corrected logRR) contains the functions used in script 1
Script 3 (Plotting of results2 - bias corrected logRR) creates figures
- for the literature review
- for comparing the grand mean and confidence intervals obtained from the treatment of missing data with the grand mean and CIs of the complete data sets