Test of Fit With the Koziol-Green Model for Random Censorship

Herbst, Thomáš

doi:10.1524/strm.1992.10.12.163

Cited by 9 publications

(5 citation statements)

References 5 publications

(6 reference statements)

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“…The properties of estimators (12) are established from the corresponding properties of estimators (4),(7), (8) and (10). In accordance with results of Cheng [7] under Conditions I we obtain asymptotic unbiasedness of , , , n n n n A A A B % % %…”

Section: Asymptotic Properties Of Estimators Of Survival Functionsupporting

confidence: 77%

“…Namely, the estimation of survival, hazard, quantile, mean and percentile residual life, total time on test, Lorenz, density and hazard rate functions is considered, and boot strapping in this model is sketched [8]. Testing the model is also discussed (see, also [10,[12][13][14]). However, it has been pointed out by many authors that the assumptions of PHM are much restrictive.…”

Section: Introductionmentioning

confidence: 99%

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On Survival Function Estimation in Dependent Partially Informative Random Censorship

Ahmedovich¹,

Baxodirovich²

2020

AJTAS

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In such areas as bio-medicine, engineering and insurance researchers are interested in positive variables, which are expressed as a time until a certain event. But observed data may be incomplete, because it is censored. Moreover, the random variables of interest (lifetimes) and censoring times can be influenced by other variable, often called prognostic factor or covariate. The basic problem is the estimation of survival function of lifetime. In this article we propose three asymptotical equivalent estimators of survival function in partially informative competing risks model. This paper deals with the estimation of a survival function with random right censoring and dependent censoring mechanism through covariate. We extend exponential-hazard, product-limit and relative-risk power estimators of survival functions in partially informative censoring model in which conditional on a covariate, the survival and censoring times are assumed to be independent. In this model, each observation is the minimum of one lifetime and two censoring times. The survival function of one of these censoring times is a power of the survival function of the lifetime. The distribution of the other censoring time has no relation with the distribution of the lifetime (non-informative censoring). For estimators we show their uniform strong consistency and convergence to same Gaussian process. Comparisons of estimators with the Jensen-Wiedmann's estimator are included.

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Section: Asymptotic Properties Of Estimators Of Survival Functionsupporting

confidence: 77%

Section: Introductionmentioning

confidence: 99%

On Survival Function Estimation in Dependent Partially Informative Random Censorship

Ahmedovich¹,

Baxodirovich²

2020

AJTAS

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“…Testing of the KG assumption is desirable in order to check whether the advantages of proportional hazards can really be used. Tests for the KG assumption itself are available in Cox (1959), Csorgo (1989), Herbst (1992), Henze (1993) and Dauxois and Kirmani (2003).…”

Section: The Sampling Designmentioning

confidence: 99%

A covariate‐adjusted adaptive design for two‐stage clinical trials with survival data

Bandyopadhyay

Biswas

Bhattacharya

2010

Statistica Neerlandica

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A randomized two-stage adaptive design is proposed and studied for allocation of patients to treatments and comparison in a phase III clinical trial with survival time as treatment responses. We consider the possibility of several covariates in the design and analysis. Several exact and limiting properties of the design and the follow-up inference are studied, both numerically and theoretically. The applicability of the proposed methodology is illustrated by using some real data.

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“…We continue the works [3] and [4], where Bayesian estimators and above all their asymptotic properties and Bayesian risk are studied. [6] deals with the asymptotic properties of the maximum likelihood estimator, in [5] a test of fit with the Koziol-Green model is given. A review of models and methods of estimation is found in [7].…”

Section: Introductionmentioning

confidence: 99%

Weak Asymptotics of the Bayes Estimator of the Reliability Function in the Koziol-Green Model

Friesl¹

2001

Statistics &Amp; Risk Modeling

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Test of Fit With the Koziol-Green Model for Random Censorship

Cited by 9 publications

References 5 publications

On Survival Function Estimation in Dependent Partially Informative Random Censorship

On Survival Function Estimation in Dependent Partially Informative Random Censorship

A covariate‐adjusted adaptive design for two‐stage clinical trials with survival data

Weak Asymptotics of the Bayes Estimator of the Reliability Function in the Koziol-Green Model

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