Literature DB >> 1594816

Designs and analysis of two-stage studies.

L P Zhao1, S Lipsitz.   

Abstract

This paper concerns the design and analysis of two-stage studies, where, at the first stage, the response and the exposure variables are available among a large group of subjects. The other covariables, however, are available in only a subset of the large group, obtained in a second-stage sample. This paper introduces a class of twelve such two-stage designs, including two-stage case-control and case-cohort designs as special cases. In analysing such two-stage data, one objective is to extract information about the relationship between the exposure variable and the response after controlling for other covariables. We discuss three statistical methods to analyse the data and report results of Monte Carlo stimulation to study the efficiency of the three methods.

Mesh:

Year:  1992        PMID: 1594816     DOI: 10.1002/sim.4780110608

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  26 in total

1.  Partial linear inference for a 2-stage outcome-dependent sampling design with a continuous outcome.

Authors:  Guoyou Qin; Haibo Zhou
Journal:  Biostatistics       Date:  2010-12-14       Impact factor: 5.899

2.  Pattern Recognition of Longitudinal Trial Data with Nonignorable Missingness: An Empirical Case Study.

Authors:  Hua Fang; Kimberly Andrews Espy; Maria L Rizzo; Christian Stopp; Sandra A Wiebe; Walter W Stroup
Journal:  Int J Inf Technol Decis Mak       Date:  2009-09-01

Review 3.  Adjustments for unmeasured confounders in pharmacoepidemiologic database studies using external information.

Authors:  Til Stürmer; Robert J Glynn; Kenneth J Rothman; Jerry Avorn; Sebastian Schneeweiss
Journal:  Med Care       Date:  2007-10       Impact factor: 2.983

4.  A Likelihood-Based Approach for Missing Genotype Data.

Authors:  Gina M D'Angelo; M Ilyas Kamboh; Eleanor Feingold
Journal:  Hum Hered       Date:  2010       Impact factor: 0.444

5.  On semiparametric efficient inference for two-stage outcome-dependent sampling with a continuous outcome.

Authors:  Rui Song; Haibo Zhou; Michael R Kosorok
Journal:  Biometrika       Date:  2009-01-26       Impact factor: 2.445

6.  Outcome-dependent sampling: an efficient sampling and inference procedure for studies with a continuous outcome.

Authors:  Haibo Zhou; Jianwei Chen; Tiina H Rissanen; Susan A Korrick; Howard Hu; Jukka T Salonen; Matthew P Longnecker
Journal:  Epidemiology       Date:  2007-07       Impact factor: 4.822

7.  Outcome- and auxiliary-dependent subsampling and its statistical inference.

Authors:  Xiaofei Wang; Yougui Wu; Haibo Zhou
Journal:  J Biopharm Stat       Date:  2009-11       Impact factor: 1.051

8.  Assessing familial aggregation of age at onset, by using estimating equations, with application to breast cancer.

Authors:  L Hsu; L P Zhao
Journal:  Am J Hum Genet       Date:  1996-05       Impact factor: 11.025

9.  Doubly-robust estimators of treatment-specific survival distributions in observational studies with stratified sampling.

Authors:  Xiaofei Bai; Anastasios A Tsiatis; Sean M O'Brien
Journal:  Biometrics       Date:  2013-10-11       Impact factor: 2.571

10.  Design and analysis of multiple events case-control studies.

Authors:  Wenguang Sun; Marshall M Joffe; Jinbo Chen; Steven M Brunelli
Journal:  Biometrics       Date:  2010-12       Impact factor: 2.571

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