Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Maximum likelihood method for linear transformation models with cohort sampling data

Language

English

Abstract

Three widely used sampling designs-the nested case-control, case-cohort, and classical case-control designs-can be categorized as generalized case-cohort designs. Maximum likelihood methods are used to perform regression analysis of linear transformation models with these sampling designs, and the resulting estimator is proved to be consistent, asymptotically normal and semiparametrically efficient. Simulation studies and an application to the Stanford heart transplant data are presented.

Keywords

Linear transformation models, Maximum likelihood estimation, Missing at random, Nested case-control sampling

Publication Date

2015

Source Publication Title

Statistica Sinica

Volume

25

Issue

3

Start Page

1231

End Page

1248

Publisher

Academia Sinica, Institute of Statistical Science

DOI

10.5705/ss.2011.194

Link to Publisher's Edition

http://dx.doi.org/10.5705/ss.2011.194

ISSN (print)

10170405

ISSN (electronic)

19968507

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