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A Quasi-Likelihood Approach for Overdispersed Binomial Data When N Is Unobserved
Jennifer A. Elder, W. Hans Carter, Jr., Chris Gennings and R. K. Elswick, Jr.
Journal of Agricultural, Biological, and Environmental Statistics
Vol. 4, No. 2 (Jun., 1999), pp. 102-115
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/1400591
Page Count: 14
You can always find the topics here!Topics: Crypts, Estimation methods, Binomials, Statistical variance, Older adults, Datasets, Statistical estimation, Standard deviation, Method of moments, Mathematical independent variables
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Several methods for the analysis of binomial data when the denominator, N, is unknown have been developed. Each of these methods requires that the mean of the distribution of N is known. In this article, we develop a quasi-likelihood technique that allows for the estimation of the means of the distributions needed to define the expected value and variance of the observed response and suggest a different form of the variance function. We illustrate the results of the proposed analysis and the results obtained when the mean of the distribution of N is assumed known through the analysis of a surviving jejunal crypt data set. Although the proposed method shows inflated standard errors of the parameter estimates in the cited example, the proposed method performs as well as a previously published method in all simulated conditions. Moreover, in cases where E(N) is misspecified, the proposed method outperforms the previously published method.
Journal of Agricultural, Biological, and Environmental Statistics © 1999 International Biometric Society