While the derivation and estimation of heterogeneous choice models appears
straightforward, the properties of such models are not well understood. We present …

In political science, there are many cases where individuals make discrete choices from
more than two alternatives. This paper uses Monte Carlo analysis to examine several …

We consider the problem of choosing between rival statistical models that are non-nested in
terms of their functional forms. We assess the ability of two tests, one parametric and one …

Theory: The spatial model of elections can better be represented by using conditional logit
models which consider the position of the parties in issue spaces than by multinomial logit …

Social scientists are often confronted with theories in which one or more actors make
choices over a discrete set of options. In this article, I generalize a broad class of statistical …

● When a binary or ordinal regression model incorrectly assumes that error variances are
the same for all cases, the standard errors are wrong and (unlike OLS regression) the …

When a binary or ordinal regression model incorrectly assumes that error variances are the
same for all cases, the standard errors are wrong and (unlike ordinary least squares …

Logit and probit, the two most common techniques for estimation of models with a
dichotomous dependent variable, impose the assumption that individuals with a probability …

Heterogeneity or the presence of a variety of decision rules in a population has usually been
ignored in voting research. A method for handling heterogeneous preferences using rank …

Political researchers are often confronted with unordered categorical variables, such as the
vote-choice of a particular voter in a multiparty election. In such situations, researchers must …