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Bayesian posterior estimation of logit parameters with small samples

Galindo-Garre, Francisca, Vermunt, Jeroen K. and Bergsma, Wicher P. (2004) Bayesian posterior estimation of logit parameters with small samples. Sociological Methods and Research, 33 (1). pp. 88-117. ISSN 0049-1241

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Identification Number: 10.1177/0049124104265997


When the sample size is small compared to the number of cells in a contingency table, maximum likelihood estimates of logit parameters and their associated standard errors may not exist or may be biased. This problem is usually solved by "smoothing" the estimates, assuming a certain prior distribution for the parameters. This article investigates the performance of point and interval estimates obtained by assuming various prior distributions. The authors focus on two logit parameters of a 2 × 2 × 2 table: the interaction effect of two predictors on a response variable and the main effect of one of two predictors on a response variable, under the assumption that the interaction effect is zero. The results indicate the superiority of the posterior mode to the posterior mean.

Item Type: Article
Official URL:
Additional Information: © 2004 SAGE Publications
Divisions: Statistics
Subjects: Q Science > QA Mathematics
Date Deposited: 01 Nov 2007
Last Modified: 16 May 2024 00:16

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