### 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 language | English (US) |
---|---|

Pages (from-to) | 2803-2819 |

Number of pages | 17 |

Journal | Communications in Statistics - Theory and Methods |

Volume | 28 |

Issue number | 12 |

State | Published - 1999 |

### Fingerprint

### Keywords

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

### ASJC Scopus subject areas

- Statistics and Probability
- Safety, Risk, Reliability and Quality

### Cite this

*Communications in Statistics - Theory and Methods*,

*28*(12), 2803-2819.

**Uniqueness of permuted treatment estimator distributions in the proportional hazards model.** / Chen, Hongzi; Piantadosi, Steven.

Research output: Contribution to journal › Article

*Communications in Statistics - Theory and Methods*, vol. 28, no. 12, pp. 2803-2819.

}

TY - JOUR

T1 - Uniqueness of permuted treatment estimator distributions in the proportional hazards model

AU - Chen, Hongzi

AU - Piantadosi, Steven

PY - 1999

Y1 - 1999

N2 - 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.

AB - 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.

KW - Partial likelihood

KW - Permutation tests

KW - Proportional hazards

KW - Randomization procedure

UR - http://www.scopus.com/inward/record.url?scp=28344432026&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=28344432026&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:28344432026

VL - 28

SP - 2803

EP - 2819

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

SN - 0361-0926

IS - 12

ER -