Which is more generalizable, powerful and interpretable in meta-analyses, mean difference or standardized mean difference?

Abstract

Background: To examine empirically whether the mean difference (MD) or the standardised mean difference (SMD) is more generalizable and statistically powerful in meta-analyses of continuous outcomes when the same unit is used. Methods. From all the Cochrane Database (March 2013), we identified systematic reviews that combined 3 or more randomised controlled trials (RCT) using the same continuous outcome. Generalizability was assessed using the I-squared (I§ssup§2§esup§) and the percentage agreement. The percentage agreement was calculated by comparing the MD or SMD of each RCT with the corresponding MD or SMD from the meta-analysis of all the other RCTs. The statistical power was estimated using Z-scores. Meta-analyses were conducted using both random-effects and fixed-effect models. Results: 1068 meta-analyses were included. The I§ssup§2§esup§ index was significantly smaller for the SMD than for the MD (P < 0.0001, sign test). For continuous outcomes, the current Cochrane reviews pooled some extremely heterogeneous results. When all these or less heterogeneous subsets of the reviews were examined, the SMD always showed a greater percentage agreement than the MD. When the I§ssup§2§esup§ index was less than 30%, the percentage agreement was 55.3% for MD and 59.8% for SMD in the random-effects model and 53.0% and 59.8%, respectively, in the fixed effect model (both P < 0.0001, sign test). Although the Z-scores were larger for MD than for SMD, there were no differences in the percentage of statistical significance between MD and SMD in either model. Conclusions: The SMD was more generalizable than the MD. The MD had a greater statistical power than the SMD but did not result in material differences. © 2014 Takeshima et al.; licensee BioMed Central Ltd.