Meta-regression sensitivity to study miscategorisation: Implications and recommendations for double-coding in meta-analysis
Shaheed Azaad, Kassandra Friebe (2025) ·
Meta-analysis enables researchers to summarise the empirical literature on a phenomenon. Often, meta-analysts also conduct theoretically motivated moderator analyses, or meta-regressions, to determine whether the magnitude of an effect depends on relevant study characteristics (e.g., the type of stimuli or measures used). To do so requires first manually extracting information from, or coding, the meta-analysed studies. Although the veracity of moderator analyses depends on the accuracy of the coding process, many researchers opt to double-code only a fraction of their studies, leaving open the possibility of coding errors in the remaining data. Here, we simulated the impact of seemingly low rates (.02, .04, and .06) of random study miscoding on meta-regressions with categorical predictors. Results indicated that miscategorisation had a larger effect in smaller meta-analyses and when mo...