نتایج جستجو برای: additive hazards model
تعداد نتایج: 2184046 فیلتر نتایج به سال:
For current status data, LIN, OAKES and YING (1998) proposed a procedure for estimation of the regression parameters in the additive hazards model that makes clever use of martingale theory. However, one of the outstanding problems posed in the paper was the issue of ef®cient estimation, as their estimators do not attain the semiparametric information bound. In this paper, we explore this issue...
In medical studies, it is often of interest to characterize the relationship between a time-to-event and covariates, not only time-independent but also time-dependent. Time-dependent covariates are generally measured intermittently and with error. Recent interests focus on the proportional hazards framework, with longitudinal data jointly modeled through a mixed effects model. However, approach...
Consider the model φ(S(z|X)) = β(z)t ~ X, where φ is a known link function, S(·|X) is the survival function of a response Y given a covariate X, ~ X = (1,X,X2, . . . ,Xp) and β(z) = (β0(z), . . . , βp(z)) t is an unknown vector of time-dependent regression coefficients. The response is subject to left truncation and right censoring. Under this model, which reduces for special choices of φ to e....
BACKGROUND Regression models for survival data have traditionally been based on the Cox regression model. However, its validity relies heavily on assumption of proportional hazards. Another restriction of the Cox model is insufficiency in dealing with time-varying covariate effects, since the regression coefficients are assumed constant. These weaknesses have generated interest in alternative a...
Interval-censored failure time data often arise in clinical trials and medical follow-up studies, and a few methods have been proposed for their regression analysis using various regression models (Finkelstein (1986); Huang (1996); Lin, Oakes, and Ying (1998); Sun (2006)). This paper proposes an estimating equation-based approach for regression analysis of interval-censored failure time data wi...
Competing risks data arise when study subjects may experience several different types of failure. It is common that the cause of failure is missing due to various reasons. Analysis of competing risks data with missing cause of failure has received considerable attention recently (Goetghebeur and Ryan (1995), Lu and Tsiatis (2001), Gao and Tsiatis (2005), among others). In this article, we study...
This paper focuses on efficient estimation, optimal rates of convergence and effective algorithms in the partly linear additive hazards regression model with current status data. We use polynomial splines to estimate both cumulative baseline hazard function with monotonicity constraint and nonparametric regression functions with no such constraint. We propose a simultaneous sieve maximum likeli...
in this paper, presenting two simple methods for ranking of efficient dmus in dea models that included to add one virtual dmu as ideal dmu and is using the additive model. note that, we use an ideal point just for comparing efficient dmus with. although these methods are simple, they have ability for ranking all efficient dmus, extreme points and the others, also they are capable of ranking the...
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