2000
DOI: 10.1002/1097-0258(20001130)19:22<3127::aid-sim784>3.0.co;2-m
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A simple method for converting an odds ratio to effect size for use in meta-analysis

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Cited by 1,089 publications
(508 citation statements)
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“…In cases where the results were presented as an odds ratio (OR), the OR was converted to the SMD using the method recommended by Chinn. 35 For those studies where the SMD estimation was not possible, due to study design or data presentation (two data points in total), the results were described independently.…”
Section: Data Extraction and Statistical Analysismentioning
confidence: 99%
“…In cases where the results were presented as an odds ratio (OR), the OR was converted to the SMD using the method recommended by Chinn. 35 For those studies where the SMD estimation was not possible, due to study design or data presentation (two data points in total), the results were described independently.…”
Section: Data Extraction and Statistical Analysismentioning
confidence: 99%
“…Chinn's method for converting an OR to effect size was used to compute SMDs of continuous outcomes that had been artificially dichotomised in primary studies [11]. Studies comparing mentally comorbid patients and patients without mental disorders using β coefficients derived from regression analyses were not included in meta-analyses due to their methodological shortcomings when used as measures of effect [12].…”
Section: Quantitative Data Analysismentioning
confidence: 99%
“…To assess the eff ect of MFQ imputation and missing covariate data on fi ndings, we did unweighted GLM with mental health service contact at T1 predicting T3 MFQ clinical cutoff (adjusted by T1 MFQ only) in three separate models: model A (raw MFQ [n=95]), model B (imputed MFQ [n=124]), and model C (imputed MFQ with missing data from propensity score weighted covariates [n=119]). Eff ect sizes (calculated from odds ratios 26 ) for mental health service contact in these models were similar (0·44 for model A, 0·46 for model B, and 0·45 for model C), indicating no eff ect of imputation or missing data.…”
Section: Resultsmentioning
confidence: 87%