Literature DB >> 17608788

Power calculation for case-cohort studies with nonrare events.

Jianwen Cai1, Donglin Zeng.   

Abstract

Case-cohort design has been advocated in many epidemiologic studies when studying rare diseases or events. In this design, with a rare event, all the events are selected for risk-factor assessment. When the event is not rare, it is desirable to consider a generalized case-cohort design, where only a fraction of events are sampled. We provide a valid test statistic to compare hazards functions between two samples for this generalized design and give a method for calculating power. Our result generalizes the result in Cai and Zeng (2004, Biometrics60, 1015-1024), and it shows numerically that efficiency loss due to sampling only part of the events is very low under nonrare-events situation.

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Year:  2007        PMID: 17608788     DOI: 10.1111/j.1541-0420.2007.00838.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  15 in total

1.  Outcome-dependent sampling with interval-censored failure time data.

Authors:  Qingning Zhou; Jianwen Cai; Haibo Zhou
Journal:  Biometrics       Date:  2017-08-03       Impact factor: 2.571

2.  Marginal hazards model for case-cohort studies with multiple disease outcomes.

Authors:  S Kang; J Cai
Journal:  Biometrika       Date:  2009-12       Impact factor: 2.445

Review 3.  Recent progresses in outcome-dependent sampling with failure time data.

Authors:  Jieli Ding; Tsui-Shan Lu; Jianwen Cai; Haibo Zhou
Journal:  Lifetime Data Anal       Date:  2016-01-13       Impact factor: 1.588

4.  More efficient estimators for case-cohort studies.

Authors:  S Kim; J Cai; W Lu
Journal:  Biometrika       Date:  2013       Impact factor: 2.445

5.  Outcome-Dependent Sampling Design and Inference for Cox's Proportional Hazards Model.

Authors:  Jichang Yu; Yanyan Liu; Jianwen Cai; Dale P Sandler; Haibo Zhou
Journal:  J Stat Plan Inference       Date:  2016-05-17       Impact factor: 1.111

6.  Statistical inference for the additive hazards model under outcome-dependent sampling.

Authors:  Jichang Yu; Yanyan Liu; Dale P Sandler; Haibo Zhou
Journal:  Can J Stat       Date:  2015-09       Impact factor: 0.875

7.  Coronary risk assessment among intermediate risk patients using a clinical and biomarker based algorithm developed and validated in two population cohorts.

Authors:  D S Cross; C A McCarty; E Hytopoulos; M Beggs; N Nolan; D S Harrington; T Hastie; R Tibshirani; R P Tracy; B M Psaty; R McClelland; P S Tsao; T Quertermous
Journal:  Curr Med Res Opin       Date:  2012-11       Impact factor: 2.580

8.  Estimating effect of environmental contaminants on women's subfecundity for the MoBa study data with an outcome-dependent sampling scheme.

Authors:  Jieli Ding; Haibo Zhou; Yanyan Liu; Jianwen Cai; Matthew P Longnecker
Journal:  Biostatistics       Date:  2014-05-07       Impact factor: 5.899

9.  Analysis of multiple survival events in generalized case-cohort designs.

Authors:  Soyoung Kim; Donglin Zeng; Jianwen Cai
Journal:  Biometrics       Date:  2018-07-10       Impact factor: 2.571

10.  Accelerated failure time model for data from outcome-dependent sampling.

Authors:  Jichang Yu; Haibo Zhou; Jianwen Cai
Journal:  Lifetime Data Anal       Date:  2020-10-12       Impact factor: 1.588

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