COMPARING AND COMBINING DATA ACROSS STUDIES - ALTERNATIVES TO SIGNIFICANCE TESTING

The need to compare and combine data quantitatively is becoming more f requent in studies of animal behaviour, ecology and conservation, Usin g a hypothetical data set, I point out some limitations of combining a nd comparing data using Null Hypothesis Significance Testing (NHST). F irst, I discuss three different aspects of data analysis that should r egularly be considered: (1) effect size estimation, (2) confidence int ervals estimation and, (3) power analysis, I then suggest meta-analysi s as a sensible alternative method to account for some Limitations of NHST. Metaanalysis is a quantitative technique for the combination and comparison of independent but similar studies, Meta-analysis allows c omparison and summary of effect sizes across studies. When testing hyp otheses framed in evolutionary theory, where small effects may have pr ofound consequences, a knowledge of the magnitude of the association m ay be as important as knowing whether the data comply with the arbitra ry, sacred and dogmatic significance criterion of p < 0,05.