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COMPARISON OF QUASI‐LIKELIHOOD MODELS FOR OVERDISPERSION
Author(s) -
III N. David Yanez,
Wilson Jeffrey R.
Publication year - 1995
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1995.tb00655.x
Subject(s) - overdispersion , maximum likelihood , quasi likelihood , statistics , restricted maximum likelihood , moment (physics) , mathematics , maximum likelihood sequence estimation , computation , econometrics , method of moments (probability theory) , computer science , algorithm , count data , poisson distribution , physics , classical mechanics , estimator
Summary Methods for modelling overdispersed data are compared. These methods are considered to be of two kinds: a likelihood based approach and a method‐of‐moments based approach. The likelihood method facilitates computation of maximum likelihood estimates which can be obtained through the same algorithm as that of weighted least squares. The quasi‐likelihood or moment approaches seem to be appropriate when severe overdispersion may be present. The comparisons are made via analyses of the Ames Salmonella Reverse Mutagenicity Assay (Margolin et a/., 1981) and a seed dataset (Crow‐der, 1978).