Cumulative sojourn time in longitudinal studies: a sequential imputation method to handle missing health state data due to dropout-Reference-Cited by-同舟云学术

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Cumulative sojourn time in longitudinal studies: a sequential imputation method to handle missing health state data due to dropout

Published:2014-01-13 Issue:12 Volume:33 Page:2030-2047
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Li Xiaodong¹,Liu Jingchen²,Duan Naihua³,Jiang Huiping⁴,Girgis Ragy⁵,Lieberman Jeffrey⁶

Affiliation:

1. NCMIS, Academy of Mathematics and Systems Science; Chinese Academy of Sciences; Beijing China

2. Department of Statistics, Columbia University; New York NY U.S.A.

3. Department of Biostatistics and Psychiatry; Columbia University; New York NY U.S.A.

4. Division of Biostatistics and Data Coordination; New York State Psychiatric Institute; New York NY U.S.A.

5. Department of Psychiatry; Columbia University; New York NY U.S.A.

6. College of Physicians and Surgeons; Columbia University; New York NY U.S.A.

Funder

National Science Foundation

National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Reference44 articles.

1. Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) Investigators. Effectiveness of antipsychotic drugs in patients with chronic schizophrenia;Lieberman;New England Journal of Medicine,2005

2. Inference and missing data;Rubin;Biometrika,1976

3. Small-sample degrees of freedom with multiple imputation;Barnard;Biometrika,1999

4. Significance levels from repeated p-values with multiply-imputed data;Li;Statistica Sinica,1991

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