Journal ArticleDOI
Semiparametric regression analysis for clustered failure time data
Tianxi Cai,Lee-Jen Wei,M. Wilcox +2 more
TLDR
In this paper, statistical methods to analyse such correlated observations are proposed for the Cox proportional hazards and odds models, and they use the data from a recent study of the genetic aetiology of alcoholism to illustrate the new procedures for estimation, prediction and model selection.Abstract:
Inference procedures based on the partial likelihood function for the Cox proportional hazards model have been generalised to the case in which the data consist of a large number of independent small groups of correlated failure time observations (Lee, Wei & Amato, 1992; Liang, Self & Chang, 1993; Cai & Prentice, 1997). However, the Cox model may not fit the data well. A class of linear transformation models, which includes the proportional hazards and odds models as special cases, has been studied extensively for univariate event times. In this paper, statistical methods to analyse such correlated observations are proposed for these models. We use the data from a recent study of the genetic aetiology of alcoholism to illustrate the new procedures for estimation, prediction and model selection.read more
Citations
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Semiparametric analysis of transformation models with censored data
TL;DR: In this article, a unified estimation procedure for the analysis of censored data using linear transformation models, which include the proportional hazards model and the proportional odds model as special cases, is proposed, which is easily implemented numerically and its validity does not rely on the assumption of independence between the covariates and the censoring variable.
Journal ArticleDOI
Cowards and Heroes: Group Loyalty in the American Civil War
Dora L. Costa,Matthew E. Kahn +1 more
TL;DR: This paper found that individual and company socioeconomic and demographic characteristics, ideology, and morale were important predictors of group loyalty in the Union Army during the Civil War in the U. S.
Journal ArticleDOI
Partial rank estimation of duration models with general forms of censoring
Shakeeb Khan,Elie Tamer +1 more
TL;DR: In this article, the authors proposed estimators for the regression coefficients in censored duration models which are distribution free, impose no parametric specification on the baseline hazard function, and can accommodate general forms of censoring.
Journal ArticleDOI
The sensitivity and specificity of markers for event times.
TL;DR: This research proposes semiparametric models that accommodate continuous tests and censoring, and extends in several respects the work by Leisenring et al. (1997) that dealt only with parametric models for binary tests and uncensored data.
Journal ArticleDOI
Weighted estimating equations for semiparametric transformation models with censored data from a case‐cohort design
TL;DR: In this paper, a case-cohort design for failure time data from the Atherosclerosis Risk in Communities (ARCC) study is presented, in which covariates are assembled only for a subco-hort randomly selected from the entire cohort, and any additional cases outside the sub-co hort.
References
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Longitudinal data analysis using generalized linear models
Kung Yee Liang,Scott L. Zeger +1 more
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Regression models and life tables (with discussion
TL;DR: The drum mallets disclosed in this article are adjustable, by the percussion player, as to balance, overall weight, head characteristics and tone production of the mallet, whereby the adjustment can be readily obtained.
Journal ArticleDOI
The Statistical Analysis of Failure Time Data.
Book
Empirical processes with applications to statistics
Galen R. Shorack,Jon A. Wellner +1 more
TL;DR: In this paper, a broad cross-section of the literature available on one-dimensional empirical processes is summarized, with emphasis on real random variable processes as well as a wide-ranging selection of applications in statistics.