PubMed · 9333342
Finite mixture models for proportions.
Abstract
Six data sets recording fetal control mortality in mouse litters are presented. The data are clearly overdispersed, and a standard approach would be to describe the data by means of a beta-binomial model or to use quasi-likelihood methods. For five of the examples, we show that beta-binomial model provides a reasonable description but that the fit can be significantly improved by using a mixture of a beta-binomial model with a binomial distribution. This mixture provides two alternative solutions, in one of which the binomial component indicates a high probability of death but is selected infrequently; this accounts for outlying litters with high mortality. The influence of the outliers on the beta-binomial fits is also demonstrated. The location and nature of the two main maxima to the likelihood are investigated through profile log-likelihoods. Comparisons are made with the performance of finite mixtures of binomial distributions.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
S P Brooks, B J Morgan, M S Ridout, S E Pack. 1997. Finite mixture models for proportions.. https://pubmed.ncbi.nlm.nih.gov/9333342/
Cite the original work for its findings. Save a collection to share your selection of sources.