Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

OBJECTIVE: For continuous outcomes measured using instruments with an established minimally important difference (MID), pooled estimates can be usefully reported in MID units. Approaches suggested thus far omit studies that used instruments without an established MID. We describe an approach that addresses this limitation. STUDY DESIGN: Using the ratio of MID to standard deviation in the trials with an established MID, we imputed the MID for instruments without an established MID and pooled across all trials. We applied this approach to two meta-analyses. RESULTS: In 20 trials of respiratory rehabilitation, the pooled estimate did not differ significantly between trials with an established MID and those without an established MID (interaction P=0.23). The same was true for 52 trials examining amitriptyline vs. other antidepressants (interaction P=0.54). In the respiratory example, the addition of trials without an established MID led to little change in point estimates or confidence intervals (CIs, more data balanced by more heterogeneity in a random effects model). In the antidepressant example, the additional trials resulted in an identical point estimate with a narrowing of the CI. CONCLUSION: Our method allows estimates of a pooled effect in MID units using both trials with and without an established MID.

Original publication

DOI

10.1016/j.jclinepi.2012.02.008

Type

Journal article

Journal

J Clin Epidemiol

Publication Date

08/2012

Volume

65

Pages

817 - 826

Keywords

Amitriptyline, Antidepressive Agents, Confidence Intervals, Data Interpretation, Statistical, Depressive Disorder, Major, Humans, Meta-Analysis as Topic, Outcome Assessment, Health Care, Pulmonary Disease, Chronic Obstructive, Quality of Life, Randomized Controlled Trials as Topic, Sample Size