Details

Autor(en) / Beteiligte

• Sterne, Jonathan A C
• White, Ian R
• Carlin, John B
• Spratt, Michael
• Royston, Patrick
• Kenward, Michael G
• Wood, Angela M
• Carpenter, James R

Titel

Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls

Ist Teil von

• BMJ (British Medical Journal), 2009-06, Vol.338 (7713), p.b2393-160

Auflage

International edition

Ort / Verlag

England: BMJ Publishing Group

Erscheinungsjahr

2009

Link zum Volltext

Quelle

Applied Social Sciences Index & Abstracts (ASSIA)

Beschreibungen/Notizen

• Missing data are unavoidable in epidemiological and clinical research but their potential to undermine the validity of research results has often been overlooked in the medical literature. Here, Sterne et al review the reasons why missing data may lead to bias and loss of information in epidemiological and clinical research. They discuss the circumstances in which multiple imputation may help by reducing bias or increasing precision, as well as describing potential pitfalls in its application. Finally, they describe the recent use and reporting of analyses using multiple imputation in general medical journals, and suggest guidelines for the conduct and reporting of such analyses.