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Goodness-of-fit test for randomly censored data based on maximum correlation

Authors: Strzalkowska-Kominiak, Ewa; Grané, Aurea;

Goodness-of-fit test for randomly censored data based on maximum correlation

Abstract

In this paper we study a goodness-of-fit test based on the maximum correlation coefficient, in the context of randomly censored data. We construct a new test statistic under general right- censoring and prove its asymptotic properties. Additionally, we study a special case, when the censoring mechanism follows the well-known Koziol-Green model. We present an extensive simulation study on the empirical power of these two versions of the test statistic, showing their ad- vantages over the widely used Pearson-type test. Finally, we apply our test to the head-and-neck cancer data.

Peer Reviewed

Keywords

Maximum correlation, Matemáticas, Kaplan-Meier estimator, Goodness-of-fit, Kaplan-Meier estimator, maximum correlation, random censoring, Classificació AMS::62 Statistics::62N Survival analysis and censored data, Random censoring, 62N01, 62N03, 62G10, 62G20, Goodness-of-fit, Estadística, random censoring, Economía, :62 Statistics::62G Nonparametric inference [Classificació AMS], Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, :Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], Classificació AMS::62 Statistics::62G Nonparametric inference, :62 Statistics::62N Survival analysis and censored data [Classificació AMS], maximum correlation

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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