Abstract
Clustered interval-censored failure time data are commonly encountered in many medical settings. In such situations, one issue that often arises in practice is that the cluster size is related to the risk for the outcome of interest. It is well-known that ignoring the informativeness of the cluster size can result in biased parameter estimates. In this article, we consider regression analysis of clustered interval-censored data with informative cluster size with the focus on semiparametric methods. For the problem, two approaches are presented and investigated. One is a within-cluster resampling procedure and the other is a weighted estimating equation approach. Unlike previously published methods, the new approaches take into account cluster sizes and heterogeneous correlation structures without imposing strong parametric assumptions. A simulation experiment is carried out to evaluate the performance of the proposed approaches and indicates that they perform well for practical situations. The approaches are applied to a lymphatic filariasis study that motivated this study.
Acknowledgements
We thank the editor and two referees for their very helpful comments and suggestions that greatly improved the paper. This work was partly supported by a NCI R01 grant to the second author.
References
1 SunJ. The statistical analysis of interval-censored failure time data. New York: Springer, 2006.Suche in Google Scholar
2 WilliamsonJ, KimHY, ManathugaA, AddissDG. Modeling survival data with informative cluster size. Stat Med2007;27:543–55.10.1002/sim.3003Suche in Google Scholar PubMed
3 CaiJ, PrenticeRL. Estimating equations for hazard ratio parameters based on correlated failure time data. Biometrics1995;82:151–64.10.1093/biomet/82.1.151Suche in Google Scholar
4 ClaytonDG, CuzickJ. Multivariate generations of the proportional hazards model. J Royal Stat Soc Ser A1985;148:82–117.10.2307/2981943Suche in Google Scholar
5 HougaardP. Modelling multivariate survival. Scand J Stat1987;14:291–304.Suche in Google Scholar
6 DunsonDB, ChenZ, HarryJ. Bayesian joint models of cluster size and subunit-specific outcomes. Biometrics2003;59:521–30.10.1111/1541-0420.00062Suche in Google Scholar PubMed
7 WilliamsonJM, DattaS, SattenGA. Marginal analyses of clustered data when cluster size is informative. Biometrics2003;59:36–42.10.1111/1541-0420.00005Suche in Google Scholar PubMed
8 LiangK, ZegerS. Longitudinal data analysis using generalized linear models. Biometrika1986;73:13–22.10.1093/biomet/73.1.13Suche in Google Scholar
9 CongX, YinG, ShenY. Marginal analysis of correlated failure time data with informative cluster size. Biometrics2007;63:663–72.10.1111/j.1541-0420.2006.00730.xSuche in Google Scholar PubMed
10 FinkelsteinDM, WolfeRA. Isotonic regression for interval censored survival data using an E-M algorithm. Communications Stat Theory Methods1986;15:2493–505.10.1080/03610928608829264Suche in Google Scholar
11 LiL. and PiZ.Rank estimation of log-linear regression with interval censored data. Lifetime data analysis2003;9:57–70.Suche in Google Scholar
12 ZhangX, SunJ. Regression analysis of clustered interval-censored failure time data with informative cluster size. Computational Statistics and Data Analysis2010;54:1817–23.10.1016/j.csda.2010.01.035Suche in Google Scholar PubMed PubMed Central
13 KimY-J. Regression analysis of clustered interval-censored data with informative cluster size. Stat Med2010;29:2956–62.10.1002/sim.4042Suche in Google Scholar PubMed
14 HuangJ, RossiniJA. Sieve estimation for the proportional odds model with interval-censoring. J Am Stat Assoc1997;92:960–7.10.1080/01621459.1997.10474050Suche in Google Scholar
15 HoffmanEB, SenPK, WeinbergCR. Within cluster resampling. Biometrika2001;88:1121–34.10.1093/biomet/88.4.1121Suche in Google Scholar
16 WeiLJ, LinDY, WeissfeldL. Regression analysis of multivariable incomplete failure time data by modeling marginal distributions. J Am Stat Assoc1989;84:1065–73.10.1080/01621459.1989.10478873Suche in Google Scholar
17 LeeEW, WeiLJ, AmatoDA. Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In KleinJP, GodPK, editors. Survival Anal State Arts. Dordrecht, Germany: Kluwer Academic; 1992:237–47.10.1007/978-94-015-7983-4_14Suche in Google Scholar
18 CoxDR. Partial likelihood. Biometrika1975;62:269–76.10.1093/biomet/62.2.269Suche in Google Scholar
19 HougaardP. Analysis of multivariate survival data. New York: Springer, 2000.10.1007/978-1-4612-1304-8Suche in Google Scholar
20 WangL, SunL, SunJ. A goodness-of-fit test for the marginal cox model for correlated interval-censored failure time data. Biometrical J2006;5:1–9.Suche in Google Scholar
©2013 by Walter de Gruyter Berlin / Boston
Artikel in diesem Heft
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Artikel in diesem Heft
- Masthead
- Masthead
- Research Articles
- Sensitivity Analysis for Causal Inference under Unmeasured Confounding and Measurement Error Problems
- Assessing the Causal Effect of Policies: An Example Using Stochastic Interventions
- Novel Point Estimation from a Semiparametric Ratio Estimator (SPRE): Long-Term Health Outcomes from Short-Term Linear Data, with Application to Weight Loss in Obesity
- Exact Nonparametric Confidence Bands for the Survivor Function
- Semiparametric Regression Analysis of Clustered Interval-Censored Failure Time Data with Informative Cluster Size
- A Weighting Analogue to Pair Matching in Propensity Score Analysis
- Alternative Monotonicity Assumptions for Improving Bounds on Natural Direct Effects
- Estimation of Risk Ratios in Cohort Studies with a Common Outcome: A Simple and Efficient Two-stage Approach
- Distance-Based Mapping of Disease Risk
- The Balanced Survivor Average Causal Effect
- Commentary
- Principal Stratification: A Broader Vision