Simulation-based power calculations for large cohort studies

被引：3

作者：

Brown, Patrick ^{[1
,2
]}

Jiang, Hedy ^{[1
]}

机构：

[1] McMaster Univ, Hamilton, ON L8S 4L8, Canada

[2] Univ Toronto, Dalla Lana Sch Publ Hlth, Toronto, ON M5S 1A1, Canada

来源：

BIOMETRICAL JOURNAL | 2010年 / 52卷 / 05期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Correlated data; Large cohort studies; Nested case-control studies; Power calculations; Survival models; EPIDEMIOLOGY; MODEL; BIG;

D O I：

10.1002/bimj.200900277

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A large number of factors can affect the statistical power and bias of analyses of data from large cohort studies, including misclassification, correlated data, follow-up time, prevalence of the risk factor of interest, and prevalence of the outcome. This paper presents a method for simulating cohorts where individual's risk is correlated within communities, recruitment is staggered over time, and outcomes are observed after different follow-up periods. Covariates and outcomes are misclassified, and Cox proportional hazards models are fit with a community-level frailty term. The effect on study power of varying effect sizes, prevalences, correlation, and misclassification are explored, as well as varying the proportion of controls in nested case-control studies.

引用

页码：604 / 615

页数：12

共 10 条

[1]

[Anonymous], 2003, STAT MODEL METHODS L

[2] Size matters: just how big is BIG? Quantifying realistic sample size requirements for human genome epidemiology [J].

Burton, Paul R. ;

Hansell, Anna L. ;

Fortier, Isabel ;

Manolio, Teri A. ;

Khoury, Muin J. ;

Little, Julian ;

Elliott, Paul .

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2009, 38 (01) :263-273

[3] CASE-CONTROL SURVIVAL ANALYSIS WITH A GENERAL SEMIPARAMETRIC SHARED FRAILTY MODEL: A PSEUDO FULL LIKELIHOOD APPROACH [J].

Gorfine, Malka ;

Zucker, David M. ;

Hsu, Li .

ANNALS OF STATISTICS, 2009, 37 (03) :1489-1517

[4] Bias From Matching on Age at Death or Censor in Nested Case-Control Studies [J].

Hein, Misty J. ;

Deddens, James A. ;

Schubauer-Berigan, Mary K. .

EPIDEMIOLOGY, 2009, 20 (03) :330-338

[5] How big is big enough for epidemiology? [J].

Kaplan, George A. .

EPIDEMIOLOGY, 2007, 18 (01) :18-20

[6] Evaluation of Cox's model and logistic regression for matched case-control data with time-dependent covariates:: a simulation study [J].

Leffondré, K ;

Abrahamowicz, M ;

Siemiatycki, J .

STATISTICS IN MEDICINE, 2003, 22 (24) :3781-3794

[7] A simulation study of sample size for multilevel logistic regression models [J].

Moineddin, Rahim ;

Matheson, Flora I. ;

Glazier, Richard H. .

BMC MEDICAL RESEARCH METHODOLOGY, 2007, 7

[8] Genetic association studies of cancer: Where do we go from here? [J].

Rebbeck, Timothy R. ;

Khoury, Muin J. ;

Potter, John D. .

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2007, 16 (05) :864-865

[9]

Woodward Mark., 1999, Epidemiology: study design and data analysis

[10]

Xu Ronghui, 2008, V24, P297

← 1 →