Multiple imputation of a randomly censored covariate improves logistic regression analysis-Reference-Cited by-同舟云学术

Multiple imputation of a randomly censored covariate improves logistic regression analysis

Published:2016-03-16 Issue:15 Volume:43 Page:2886-2896
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Atem Folefac D.¹,Qian Jing²,Maye Jacqueline E.³,Johnson Keith A.⁴,Betensky Rebecca A.¹

Affiliation:

1. Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA

2. Public Health, University of Massachusetts, Amherst, MA, USA

3. Clinical and Health Psychology, University of Florida, Gainesville, FL, USA

4. Radiology, Massachusetts General Hospital, Boston, MA, USA

Funder

National Institutes of Health

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2016.1155110

Reference30 articles.

1. F.D. Atem, J. Qian, J.E. Maye, K.A. Johnson, and R.A. Betensky, Linear regression with a randomly censored covariate: Application to an Alzheimer's study, 2015, submitted.

2. Structural brain changes in normal individuals with a maternal history of Alzheimer's

3. Estimating the odds ratio when exposure has a limit of detection

4. An index approach for the Cox model with left censored covariates

5. A comparison of familial and sporadic Alzheimer's disease

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