AM Wood

AR Donders

B Winblad

BG Feagan

C Ballard

Craig R Ramsay

D Curran

D Moher

DL Fairclough

EM Hunkeler

G Molenberghs

GL Gadbury

Graeme Maclennan

J Fairbank

JA Blumenthal

JG Wright

Jonathan A Cook

JR Carpenter

JR Korzenik

JR Ware

KJ Thomas

KS Nair

L Petersen

L- Yu

LL Hsieh

M Buszewicz

M Liu

MA Berry

MG Kenward

PM Fayers

R Brooks

RC Petersen

RJ McManus

RJA Little

SA Kaplan

Shona Fielding

SJ Meggitt

T Kennedy

Trials

English

PubMed

Springer - Publisher Connector

A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes

BACKGROUND: Randomised controlled trials (RCTs) are perceived as the gold-standard method for evaluating healthcare interventions, and increasingly include quality of life (QoL) measures. The observed results are susceptible to bias if a substantial proportion of outcome data are missing. The review aimed to determine whether imputation was used to deal with missing QoL outcomes. METHODS: A random selection of 285 RCTs published during 2005/6 in the British Medical Journal, Lancet, New England Journal of Medicine and Journal of American Medical Association were identified. RESULTS: QoL outcomes were reported in 61 (21%) trials. Six (10%) reported having no missing data, 20 (33%) reported 20% missing. Missingness was unclear in 13 (21%). Missing data were imputed in 19 (31%) of the 61 trials. Imputation was part of the primary analysis in 13 trials, but a sensitivity analysis in six. Last value carried forward was used in 12 trials and multiple imputation in two. Following imputation, the most common analysis method was analysis of covariance (10 trials). CONCLUSION: The majority of studies did not impute missing data and carried out a complete-case analysis. For those studies that did impute missing data, researchers tended to prefer simpler methods of imputation, despite more sophisticated methods being available

Fielding, S

Maclennan, G

Cook, JA

Ramsay, CR

Oxford University Research Archive (ORA)

A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes.

Abstract Background Randomised controlled trials (RCTs) are perceived as the gold-standard method for evaluating healthcare interventions, and increasingly include quality of life (QoL) measures. The observed results are susceptible to bias if a substantial proportion of outcome data are missing. The review aimed to determine whether imputation was used to deal with missing QoL outcomes. Methods A random selection of 285 RCTs published during 2005/6 in the British Medical Journal, Lancet, New England Journal of Medicine and Journal of American Medical Association were identified. Results QoL outcomes were reported in 61 (21%) trials. Six (10%) reported having no missing data, 20 (33%) reported ≤ 10% missing, eleven (18%) 11%–20% missing, and eleven (18%) reported >20% missing. Missingness was unclear in 13 (21%). Missing data were imputed in 19 (31%) of the 61 trials. Imputation was part of the primary analysis in 13 trials, but a sensitivity analysis in six. Last value carried forward was used in 12 trials and multiple imputation in two. Following imputation, the most common analysis method was analysis of covariance (10 trials). Conclusion The majority of studies did not impute missing data and carried out a complete-case analysis. For those studies that did impute missing data, researchers tended to prefer simpler methods of imputation, despite more sophisticated methods being available.</p

Cook Jonathan A

Maclennan Graeme

Fielding Shona

Ramsay Craig R

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Fielding, Shona

MacLennan, Graeme Stewart

Cook, Jonathan A

Ramsay, Craig R

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A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes

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