### Abstract

Summary: Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. An on-going randomized clinical trial motivated the development of the estimator and is used to illustrate the approach.

Original language | English (US) |
---|---|

Pages (from-to) | 657-671 |

Number of pages | 15 |

Journal | Journal of the Royal Statistical Society. Series C: Applied Statistics |

Volume | 59 |

Issue number | 4 |

DOIs | |

State | Published - Aug 2010 |

### Fingerprint

### Keywords

- Binomial distribution
- Confidence interval
- Coverage probability
- Median unbiased estimator
- Relative risk
- Shrinkage estimator

### ASJC Scopus subject areas

- Statistics and Probability
- Statistics, Probability and Uncertainty

### Cite this

*Journal of the Royal Statistical Society. Series C: Applied Statistics*,

*59*(4), 657-671. https://doi.org/10.1111/j.1467-9876.2010.00711.x

**Relative risk estimated from the ratio of two median unbiased estimates.** / Carter, Rickey E.; Lin, Yan; Lipsitz, Stuart R.; Newcombe, Robert G.; Hermayer, Kathie L.

Research output: Contribution to journal › Article

*Journal of the Royal Statistical Society. Series C: Applied Statistics*, vol. 59, no. 4, pp. 657-671. https://doi.org/10.1111/j.1467-9876.2010.00711.x

}

TY - JOUR

T1 - Relative risk estimated from the ratio of two median unbiased estimates

AU - Carter, Rickey E.

AU - Lin, Yan

AU - Lipsitz, Stuart R.

AU - Newcombe, Robert G.

AU - Hermayer, Kathie L.

PY - 2010/8

Y1 - 2010/8

N2 - Summary: Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. An on-going randomized clinical trial motivated the development of the estimator and is used to illustrate the approach.

AB - Summary: Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. An on-going randomized clinical trial motivated the development of the estimator and is used to illustrate the approach.

KW - Binomial distribution

KW - Confidence interval

KW - Coverage probability

KW - Median unbiased estimator

KW - Relative risk

KW - Shrinkage estimator

UR - http://www.scopus.com/inward/record.url?scp=77955084788&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77955084788&partnerID=8YFLogxK

U2 - 10.1111/j.1467-9876.2010.00711.x

DO - 10.1111/j.1467-9876.2010.00711.x

M3 - Article

AN - SCOPUS:77955084788

VL - 59

SP - 657

EP - 671

JO - Journal of the Royal Statistical Society. Series C: Applied Statistics

JF - Journal of the Royal Statistical Society. Series C: Applied Statistics

SN - 0035-9254

IS - 4

ER -