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Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis

2020· article· en· 881 citations· W3003238214 on OpenAlex· 10.1177/0962280219889080

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Abstract

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data.

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The record

Venue
Pure Amsterdam UMC
Topic
Hemodynamic Monitoring and Therapy
Field
Medicine
Canadian institutions
Funders
Canadian Arthritis NetworkEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Mental HealthHealth Research Council of New ZealandNational Health and Medical Research CouncilMedical Research CouncilNational Center for Medical Rehabilitation ResearchFonds de Recherche du Québec - SantéNational Institute on Disability and Rehabilitation ResearchAgency for Healthcare Research and QualityMcGill University Health CentreNational Institutes of HealthNational Institute of General Medical SciencesH. Lundbeck A/SCenters for Disease Control and PreventionChinese Diabetes SocietyAlberta Health ServicesJewish General HospitalAlberta InnovatesCumming School of Medicine, University of CalgaryUniversidade de MacauSafe Work AustraliaNational Heart, Lung, and Blood InstituteTehran University of Medical Sciences and Health ServicesBundesministerium für Bildung und ForschungDeutsche RentenversicherungNational Institute on Minority Health and Health DisparitiesMcGill UniversityEli Lilly and CompanyFogarty International CenterCanadian Institutes of Health ResearchUniversity of WashingtonFaculty of Medicine, McGill UniversityOhio Board of Regents
Keywords
Standard deviationStatisticsQuartileQuantileStandard errorSample size determinationSample mean and sample covarianceMeta-analysisPooled varianceNormal distributionSample (material)MathematicsEconometricsMedicineConfidence intervalEstimator
Has abstract in OpenAlex
yes