Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates.

Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Research Abstract Details 

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Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Abstract Text:

Feng Gao,Amita K Manatunga,Shande Chen,

Often in many biomedical and epidemiologic studies, estimating hazards function is of interest. The Breslow's estimator is commonly used for estimating the integrated baseline hazard, but this estimator requires the functional form of covariate effects to be correctly specified. It is generally difficult to identify the true functional form of covariate effects in the presence of time-dependent covariates. To provide a complementary method to the traditional proportional hazard model, we propose a tree-type method which enables simultaneously estimating both baseline hazards function and the effects of time-dependent covariates. Our interest will be focused on exploring the potential data structures rather than formal hypothesis testing. The proposed method approximates the baseline hazards and covariate effects with step-functions. The jump points in time and in covariate space are searched via an algorithm based on the improvement of the full log-likelihood function. In contrast to most other estimating methods, the proposed method estimates the hazards function rather than integrated hazards. The method is applied to model the risk of withdrawal in a clinical trial that evaluates the anti-depression treatment in preventing the development of clinical depression. Finally, the performance of the method is evaluated by several simulation studies.

Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Publishing Authors By Initials

F Gao,AK Manatunga,S Chen,

For similar investigative techniques: epidemiologic methods: statistics as topic: statistics, nonparametric research abstracts see: investigative techniques: epidemiologic methods: statistics as topic: statistics, nonparametric research

PUBMED ID PMID:

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Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Statistics in medicine

VOLUME: 26

Page Numbers: 857-68

Journal Abbreviation:

ISSN: 0277-6715

DAY: 20

MONTH: Feb

YEAR: 2007

Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 8215016

Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Keywords Mesh Terms:

KEYWORDS: Statistics, Nonparametric

MESH TERMS: psychology

Chemical & Substance for Abstract: Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates. Information

Substance Name: Paroxetine

Registry Number: 61869-08-7

Grant and Affiliation Information for Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates.

AFFILIATION: Division of Biostatistics, Washington University School of Medicine, Campus Box 8067, 660 S. Euclid Ave., St Louis, MO 63110, USA.

Country: England

AGENCY: United States NIEHS

GRANT: R01-ES012458-01

ACRONYM: ES

MEDLINETA: Stat Med

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