The Annals of Statistics

Chi-Square Goodness-if-Fit Tests for Randomly Censored Data

M. G. Habib and D. R. Thomas

Full-text: Open access

Abstract

Two Pearson-type goodness-of-fit test statistics for parametric families are considered for randomly right-censored data. Asymptotic distribution theory for the test statistics is based on the result that the product-limit process with MLE for nuisance parameters converges weakly to a Gaussian process. The Chernoff-Lehmann (1954) result extends to a generalized Pearson statistic. A modified Pearson statistic is shown to have a limiting chi-square null distribution.

Article information

Source
Ann. Statist., Volume 14, Number 2 (1986), 759-765.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349953

Digital Object Identifier
doi:10.1214/aos/1176349953

Mathematical Reviews number (MathSciNet)
MR840529

Zentralblatt MATH identifier
0633.62041

JSTOR
links.jstor.org

Subjects
Primary: 62G10: Hypothesis testing
Secondary: 62E20: Asymptotic distribution theory

Keywords
Goodness-of-fit chi-square tests censored data product-limit process

Citation

Habib, M. G.; Thomas, D. R. Chi-Square Goodness-if-Fit Tests for Randomly Censored Data. Ann. Statist. 14 (1986), no. 2, 759--765. doi:10.1214/aos/1176349953. https://projecteuclid.org/euclid.aos/1176349953


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