When continuous outcomes are measured using different scales: Guide for meta-analysis and interpretation

Mohammad Hassan Murad, Zhen Wang, Haitao Chu, Lifeng Lin

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

It is common to measure continuous outcomes using different scales (eg, quality of life, severity of anxiety or depression), therefore these outcomes need to be standardized before pooling in a meta-analysis. Common methods of standardization include using the standardized mean difference, the odds ratio derived from continuous data, the minimally important difference, and the ratio of means. Other ways of making data more meaningful to end users include transforming standardized effects back to original scales and transforming odds ratios to absolute effects using an assumed baseline risk. For these methods to be valid, the scales or instruments being combined across studies need to have assessed the same or a similar construct

Original languageEnglish (US)
Article numberk4817
JournalBMJ (Online)
Volume364
DOIs
StatePublished - Jan 22 2019

Bibliographical note

Funding Information:
Funding: This research did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector. HC is supported in part by the National Library of Medicine (R21 LM012197, R21 LM012744), and the National Institute of Diabetes and Digestive and Kidney Diseases (U01 DK106786). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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