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'Smooth' inference for survival functions with arbitrarily censored data.

Publication ,  Journal Article
Doehler, K; Davidian, M
Published in: Stat Med
November 20, 2008

We propose a procedure for estimating the survival function of a time-to-event random variable under arbitrary patterns of censoring. The method is predicated on the mild assumption that the distribution of the random variable, and hence the survival function, has a density that lies in a class of 'smooth' densities whose elements can be represented by an infinite Hermite series. Truncation of the series yields a 'parametric' expression that can well approximate any plausible survival density, and hence survival function, provided the degree of truncation is suitably chosen. The representation admits a convenient expression for the likelihood for the 'parameters' in the approximation under arbitrary censoring/truncation that is straightforward to compute and maximize. A test statistic for comparing two survival functions, which is based on an integrated weighted difference of estimates of each under this representation, is proposed. Via simulation studies and application to a number of data sets, we demonstrate that the approach yields reliable inferences and can result in gains in efficiency over traditional nonparametric methods.

Duke Scholars

Published In

Stat Med

DOI

ISSN

0277-6715

Publication Date

November 20, 2008

Volume

27

Issue

26

Start / End Page

5421 / 5439

Location

England

Related Subject Headings

  • Survival Analysis
  • Statistics, Nonparametric
  • Statistics & Probability
  • Likelihood Functions
  • Humans
  • Endpoint Determination
  • Disease Progression
  • Data Interpretation, Statistical
  • Computer Simulation
  • Clinical Trials as Topic
 

Citation

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Doehler, K., & Davidian, M. (2008). 'Smooth' inference for survival functions with arbitrarily censored data. Stat Med, 27(26), 5421–5439. https://doi.org/10.1002/sim.3368
Doehler, Kirsten, and Marie Davidian. “'Smooth' inference for survival functions with arbitrarily censored data.Stat Med 27, no. 26 (November 20, 2008): 5421–39. https://doi.org/10.1002/sim.3368.
Doehler K, Davidian M. 'Smooth' inference for survival functions with arbitrarily censored data. Stat Med. 2008 Nov 20;27(26):5421–39.
Doehler, Kirsten, and Marie Davidian. “'Smooth' inference for survival functions with arbitrarily censored data.Stat Med, vol. 27, no. 26, Nov. 2008, pp. 5421–39. Pubmed, doi:10.1002/sim.3368.
Doehler K, Davidian M. 'Smooth' inference for survival functions with arbitrarily censored data. Stat Med. 2008 Nov 20;27(26):5421–5439.
Journal cover image

Published In

Stat Med

DOI

ISSN

0277-6715

Publication Date

November 20, 2008

Volume

27

Issue

26

Start / End Page

5421 / 5439

Location

England

Related Subject Headings

  • Survival Analysis
  • Statistics, Nonparametric
  • Statistics & Probability
  • Likelihood Functions
  • Humans
  • Endpoint Determination
  • Disease Progression
  • Data Interpretation, Statistical
  • Computer Simulation
  • Clinical Trials as Topic