Monte Carlo exact tests for log-linear and logistic models.
Forster, Jonathan J., McDonald, John W. and Smith, Peter W.F. (1996) Monte Carlo exact tests for log-linear and logistic models. Journal of the Royal Statistical Society. Series B (Methodological), 58, (2), 445-453.
Full text not available from this repository.
The form of the exact conditional distribution of a sufficient statistic for the interest parameters, given a sufficient statistic for the nuisance parameters, is derived for a generalized linear model with canonical link. General results for log-linear and logistic models are given. A Gibbs sampling approach for generating from the conditional distribution is proposed, which enables Monte Carlo exact conditional tests to be performed. Examples include tests for goodness of fit of the all-two-way interaction model for a 28-table and of a simple logistic model. Tests against non-saturated alternatives are also considered.
|Subjects:||Q Science > QA Mathematics|
|Divisions:||University Structure - Pre August 2011 > School of Mathematics > Statistics
|Date Deposited:||19 Mar 2007|
|Last Modified:||01 Jun 2011 02:10|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)