### Abstract

This paper is concerned with testing the multinomial (binomial) assumption against the Dirichlet-multinomial (beta-binomial) alternatives. In particular, we discuss the distribution of the asymptotic likelihood ratio (LR) test and obtain the C(alpha) goodness-of-fit test statistic. The inadequacy of the regular chi-square approximation to the LR test is supported by some Monte Carlo experiments. The C(alpha) test is recommended based on empirical significance level and power and also computational simplicity. Two examples are given.

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

Pages (from-to) | 231-236 |

Number of pages | 6 |

Journal | Biometrics |

Volume | 45 |

Issue number | 1 |

State | Published - Mar 1989 |

Externally published | Yes |

### Fingerprint

### ASJC Scopus subject areas

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

### Cite this

*Biometrics*,

*45*(1), 231-236.

**On testing departure from the binomial and multinomial assumptions.** / Paul, S. R.; Liang, K. Y.; Self, S. G.

Research output: Contribution to journal › Article

*Biometrics*, vol. 45, no. 1, pp. 231-236.

}

TY - JOUR

T1 - On testing departure from the binomial and multinomial assumptions.

AU - Paul, S. R.

AU - Liang, K. Y.

AU - Self, S. G.

PY - 1989/3

Y1 - 1989/3

N2 - This paper is concerned with testing the multinomial (binomial) assumption against the Dirichlet-multinomial (beta-binomial) alternatives. In particular, we discuss the distribution of the asymptotic likelihood ratio (LR) test and obtain the C(alpha) goodness-of-fit test statistic. The inadequacy of the regular chi-square approximation to the LR test is supported by some Monte Carlo experiments. The C(alpha) test is recommended based on empirical significance level and power and also computational simplicity. Two examples are given.

AB - This paper is concerned with testing the multinomial (binomial) assumption against the Dirichlet-multinomial (beta-binomial) alternatives. In particular, we discuss the distribution of the asymptotic likelihood ratio (LR) test and obtain the C(alpha) goodness-of-fit test statistic. The inadequacy of the regular chi-square approximation to the LR test is supported by some Monte Carlo experiments. The C(alpha) test is recommended based on empirical significance level and power and also computational simplicity. Two examples are given.

UR - http://www.scopus.com/inward/record.url?scp=0024633406&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024633406&partnerID=8YFLogxK

M3 - Article

C2 - 2720053

AN - SCOPUS:0024633406

VL - 45

SP - 231

EP - 236

JO - Biometrics

JF - Biometrics

SN - 0006-341X

IS - 1

ER -