Two-stage sampling usually leads to higher variances for estimators of means and regression coefficients, because of intra-cluster homogeneity. One way of allowing for clustering in fitting a linear regression model is to use a linear mixed model with two levels. If the estimated intra-cluster...

The phenomenon of overdispersion arises when categorical or count data exhibit variability larger than expected. Multinomial data commonly demonstrate this phenomenon when the counts arise from correlated or cluster observations. There are several ways of analyzing overdispersed multinomial...

This article will survey issues in analyzing complex survey data and describe some of the capabilities of Stata for such analyses. We will briefly review key elements of survey design and explain the effects of different design features on bias and variance. We compare different methods of...

In this article, various issues related to the implementation of the usual Bayesian Information Criterion (BIC) are critically examined in the context of modelling a finite population. A suitable design-based approximation to the BIC is proposed in order to avoid the derivation of the exact...

New recursive algorithms for fast computation of the normalizing constant for the autologistic model on the lattice make feasible a sample-based maximum likelihood estimation (MLE) of the autologistic parameters. We demonstrate by sampling from 12 simulated 420×420 binary lattices with square...