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Large variation existed in standardized mean difference estimates using different calculation methods in clinical

Yan Luo1, Satoshi Funada2, Kazufumi Yoshida1

  • 1Department of Health Promotion and Human Behaviour, School of Public Health in the Graduate School of Medicine, Kyoto University, Yoshida Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan.

Journal of Clinical Epidemiology
|June 2, 2022
PubMed
Summary
This summary is machine-generated.

Standardized mean difference (SMD) calculations varied significantly across studies due to different mean differences (MDs) and standard deviations (SDs). Insufficient reporting and oversimplified interpretations of SMD were common, risking bias.

Keywords:
Cohen's dContinuous outcomeEffect measureEffect sizeResearch methodologyStandard effect sizeStandardized mean difference

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Area of Science:

  • Biostatistics
  • Clinical Trial Methodology
  • Evidence Synthesis

Background:

  • Standardized Mean Difference (SMD) is a crucial effect size metric in meta-analyses.
  • Calculating SMD involves Mean Differences (MDs) and Standard Deviations (SDs), with potential for variation.
  • Inconsistent reporting and interpretation of SMD can impact research validity.

Purpose of the Study:

  • To investigate the calculation, reporting, and interpretation of SMD in clinical trials.
  • To examine the variability of SMD estimates derived from different MDs and SDs within single studies.
  • To identify potential biases and misinterpretations in SMD reporting.

Main Methods:

  • Systematic search of PubMed for randomized controlled trials in general medicine and psychiatry that reported SMD.
  • Exploration of SMD computation and interpretation methods used in the selected studies.
  • Calculation of SMDs using alternative MDs and SDs from study data to assess variability.

Main Results:

  • 161 articles were analyzed, with 69.0% lacking sufficient detail on SMD calculation.
  • Substantial variations in SMD estimates were observed (median absolute difference: 0.3).
  • Most studies (68.3%) used Cohen's rule of thumb for interpretation, with larger variations in small sample size studies.

Conclusions:

  • SMD calculations and reporting often lack transparency, leading to considerable variability.
  • Oversimplified interpretation of SMD, particularly using Cohen's rule of thumb, is prevalent.
  • Prespecification of methods and multi-perspective interpretation are recommended to mitigate bias and misinterpretation.