Analysis of binary outcomes with missing data: missing = smoking, last observation carried forward, and a little multiple imputation

Addiction - Tập 102 Số 10 - Trang 1564-1573 - 2007
Donald Hedeker1, Robin J. Mermelstein1, Hakan Demirtaş1
1University of Illinois at Chicago, Chicago, IL USA

Tóm tắt

ABSTRACTAims  Analysis of binary outcomes with missing data is a challenging problem in substance abuse studies. We consider this problem in a simple two‐group design where interest centers on comparing the groups in terms of the binary outcome at a single timepoint.Design  We describe how the deterministic assumptions of missing = smoking and last observation carried forward (LOCF) can be relaxed by allowing missingness to be related imperfectly to the binary outcome, either stratified on past values of the outcome or not. We also describe use of multiple imputation to take into account the uncertainty inherent in the imputed data.Setting  Data were analyzed from a published smoking cessation study evaluating the effectiveness of adding group‐based treatment adjuncts to an intervention comprised of a television program and self‐help materials.Participants  Participants were 489 smokers who registered for the television‐based program and who indicated an interest in attending group‐based meetings.Measurements  The measurement of the smoking outcome was conducted via telephone interviews at post‐intervention and at 24 months.Findings and conclusions  The significance of the group effect did vary as a function of the assumed relationship between missingness and smoking. The ‘conservative’ missing = smoking assumption suggested a beneficial group effect on smoking cessation, which was confirmed via a sensitivity analysis only if an extreme odds ratio of 5 between missingness and smoking was assumed. This type of sensitivity analysis is crucial in determining the role that missing data play in arriving at a study's conclusions.

Từ khóa


Tài liệu tham khảo

10.1037/0022-006X.62.3.569

10.1080/14622200110050411

10.2307/2532847

10.1037/1082-989X.7.2.147

10.1111/j.0006-341X.2004.00234.x

10.1002/9781119013563

10.1097/01.yco.0000133836.34543.7e

10.1037/1082-989X.6.4.330

10.1046/j.1467-789X.2003.00109.x

10.1002/0471264385.wei0204

10.1016/j.drugalcdep.2004.08.018

10.1093/biomet/63.3.581

10.1002/sim.4780070131

10.1016/S0376-8716(02)00111-4

10.1037/0022-006X.61.1.113

10.1037/1082-989X.3.2.147

Long J. S., 1997, Regression Models for Categorical and Limited Dependent Variables

10.1002/0471249688

10.1201/9781439821862

10.1037/0022-006X.71.3.565

10.1023/A:1010375931040

10.1037/1082-989X.6.4.317

10.1046/j.1360-0443.91.12s1.11.x

10.1046/j.1360-0443.95.11s3.7.x

10.1002/sim.2117

Thông tin
Thông tin xuất bản

Addiction

Tập 102 Số 10

1564-1573

Thông tin tác giả