### Abstract

When faced with proportion data that exhibit extra-binomial variation, data analysts often consider the beta-binomial distribution as an alternative model to the more common binomial distribution. A typical example occurs in toxicological experiments with laboratory animals, where binary observations on fetuses within a litter are often correlated with each other. In such instances, it may be of interest to test for the goodness of fit of the beta-binomial model; this effort is complicated, however, when there is large variability among the litter sizes. We investigate a recent goodness-of-fit test proposed by Brooks et al. (1997, Biometrics 53, 1097-1115) but find that it lacks the ability to distinguish between the beta-binomial model and some severely non-beta-binomial models. Other tests and models developed in their article are quite useful and interesting but are not examined herein.

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

Pages (from-to) | 947-950 |

Number of pages | 4 |

Journal | Biometrics |

Volume | 56 |

Issue number | 3 |

State | Published - 2000 |

Externally published | Yes |

### Fingerprint

### Keywords

- Beta-binomial
- Goodness-of-fit
- Likelihood
- Overdispersion
- Pearson statistic

### ASJC Scopus subject areas

- Agricultural and Biological Sciences(all)
- Public Health, Environmental and Occupational Health
- Agricultural and Biological Sciences (miscellaneous)
- Applied Mathematics
- Statistics and Probability

### Cite this

*Biometrics*,

*56*(3), 947-950.

**On a likelihood-based goodness-of-fit test of the beta-binomial model.** / Garren, S. T.; Smith, R. L.; Piegorsch, Walter W; Brooks, S.; Morgan, B.; Ridout, M.

Research output: Contribution to journal › Article

*Biometrics*, vol. 56, no. 3, pp. 947-950.

}

TY - JOUR

T1 - On a likelihood-based goodness-of-fit test of the beta-binomial model

AU - Garren, S. T.

AU - Smith, R. L.

AU - Piegorsch, Walter W

AU - Brooks, S.

AU - Morgan, B.

AU - Ridout, M.

PY - 2000

Y1 - 2000

N2 - When faced with proportion data that exhibit extra-binomial variation, data analysts often consider the beta-binomial distribution as an alternative model to the more common binomial distribution. A typical example occurs in toxicological experiments with laboratory animals, where binary observations on fetuses within a litter are often correlated with each other. In such instances, it may be of interest to test for the goodness of fit of the beta-binomial model; this effort is complicated, however, when there is large variability among the litter sizes. We investigate a recent goodness-of-fit test proposed by Brooks et al. (1997, Biometrics 53, 1097-1115) but find that it lacks the ability to distinguish between the beta-binomial model and some severely non-beta-binomial models. Other tests and models developed in their article are quite useful and interesting but are not examined herein.

AB - When faced with proportion data that exhibit extra-binomial variation, data analysts often consider the beta-binomial distribution as an alternative model to the more common binomial distribution. A typical example occurs in toxicological experiments with laboratory animals, where binary observations on fetuses within a litter are often correlated with each other. In such instances, it may be of interest to test for the goodness of fit of the beta-binomial model; this effort is complicated, however, when there is large variability among the litter sizes. We investigate a recent goodness-of-fit test proposed by Brooks et al. (1997, Biometrics 53, 1097-1115) but find that it lacks the ability to distinguish between the beta-binomial model and some severely non-beta-binomial models. Other tests and models developed in their article are quite useful and interesting but are not examined herein.

KW - Beta-binomial

KW - Goodness-of-fit

KW - Likelihood

KW - Overdispersion

KW - Pearson statistic

UR - http://www.scopus.com/inward/record.url?scp=0033851664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033851664&partnerID=8YFLogxK

M3 - Article

C2 - 10985242

AN - SCOPUS:0033851664

VL - 56

SP - 947

EP - 950

JO - Biometrics

JF - Biometrics

SN - 0006-341X

IS - 3

ER -