Probabilistic feature models (PFMs) can be used to explain binary rater judgements about the associations between two types of elements (e.g., objects and attributes) on the basis of binary latent features. In particular, to explain observed object-attribute associations PFMs assume that...

The nature of ethnic residential clustering involves different population segments which through their location decisions influence the spatial patterns of ethnic settlements. Understanding the differences in the residential behaviour of a heterogeneous population and, in particular, the tastes...

A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students’ response to...

Random-effects change point models are formulated for longitudinal data obtained from cognitive tests. The conditional distribution of the response variable in a change point model is often assumed to be normal even if the response variable is discrete and shows ceiling effects. For the sum...

I exploit the potential of latent class models for proposing an innovative framework for financial data analysis. By stressing the latent nature of the most important financial variables, expected return and risk, I am able to introduce a new methodological dimension in the analysis of financial...

In this article, we describe lclogit, a Stata command for fitting a discrete-mixture or latent-class logit model via the expectation-maximization algorithm. Copyright 2013 by StataCorp LP.

Payments for ecosystem services (PES) programs aim to improve environmental outcomes by providing direct incentives to land managers for the provision of ecosystem services. Participation in PES programs is voluntary, so effective program design requires careful consideration of farmers'...