Literature DB >> 2720053

On testing departure from the binomial and multinomial assumptions.

S R Paul1, K Y Liang, S G Self.   

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.

Mesh:

Year:  1989        PMID: 2720053

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  4 in total

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Review 2.  Statistical methods for the beta-binomial model in teratology.

Authors:  E Yamamoto; T Yanagimoto
Journal:  Environ Health Perspect       Date:  1994-01       Impact factor: 9.031

3.  Pooling overdispersed binomial data to estimate event rate.

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Journal:  BMC Med Res Methodol       Date:  2008-08-19       Impact factor: 4.615

4.  A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification.

Authors:  Francesco Bartolucci; Fulvia Pennoni; Antonietta Mira
Journal:  Stat Med       Date:  2021-08-10       Impact factor: 2.497

  4 in total

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