Uniqueness of permuted treatment estimator distributions in the proportional hazards model

Hongzi Chen, Steven Piantadosi

    Research output: Contribution to journalArticle

    Abstract

    We discuss findings regarding the permutation distributions of treatment effect estimators in the proportional hazards model. For fixed sample size n, we will prove that all uncensored and untied event times yield the same permutation distribution of treatment effect estimators in the proportional hazards model. In other words this distribution is irrelevant with respect to the actual event times. We will show several uniqueness properties under different conditions. These properties are useful for small sample permutation tests and also helpful to large sample cases.

    Original languageEnglish (US)
    Pages (from-to)2803-2819
    Number of pages17
    JournalCommunications in Statistics - Theory and Methods
    Volume28
    Issue number12
    DOIs
    StatePublished - Jan 1 1999

    Keywords

    • Partial likelihood
    • Permutation tests
    • Proportional hazards
    • Randomization procedure

    ASJC Scopus subject areas

    • Statistics and Probability

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