Meta-analysis on continuous outcomes in minimal important difference units: an application with appropriate variance calculations
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Updated: Mar 17, 2026

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Published on: April 19, 2024
Ian Shrier1, Robin Christensen2, Carsten Juhl3
1Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, McGill University, 3755 Cote Ste-Catherine Road, Montreal, Quebec H3T 1E2, Canada.
Objective:
To compare results from meta-analyses for mean differences in minimal important difference (MID) units (MDMID), when MID is treated as a random variable vs. a constant.
Study Design And Setting:
Meta-analyses of published data. We calculated the variance of MDMID as a random variable using the delta method and as a constant. We assessed performance under different assumptions. We compare meta-analysis results from data originally used to present the MDMID and data from osteoarthritis studies using different domain instruments.
Results:
Depending on the data set and depending on the values of rho and coefficient of variation of the MID (CoVMID), estimates of treatment effect and P-values between an approach considering the MID as a constant vs. as a random variable may differ appreciably. Using our data sets, we provide examples of the potential magnitude. When rho = 0.5 and CoVMID = 0.8, considering MID as a constant overestimated the treatment effect by 33-110% and decreased the P-value for heterogeneity from above 0.95 to below 0.08. When rho = 0.8 and CoVMID = 0.5, the magnitude of the effects was similar.
Conclusions:
Considering MID as a random variable avoids unrealistic assumptions and provides more appropriate treatment effect estimates.
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