Consider the case in which we have data from repeated surveys covering several geographic areas, and our goal is to characterize these areas on a latent trait that underlies multiple indicators. This characterization occurs, for example, in surveys of information and communication technologies...

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LF and WF). The two formats suggest two alternative model approaches for analyzing panel data: (i) univariate regression with varying intercept; and (ii) multivariate regression with latent variables (a...

Standard methods for the analysis of linear latent variable models often rely on the assumption that the vector of observed variables is normally distributed. This normality assumption (NA) plays a crucial role in assessing optimality of estimates, in computing standard errors, and in designing...

"Beauty-contest" is a game in which participants have to choose, typically, a number in [0,100], the winner being the person whose number is closest to a proportion of the average of all chosen numbers. We describe and analyze Beauty-contest experiments run in newspapers in UK, Spain, and...

This work is part of a project studying the performance of model based estimators in a small area context. We have chosen a simple statistical application in which we estimate the growth rate of accupation for several regions of Spain. We compare three estimators: the direct one based on...

This paper investigates the comparative performance of five small area estimators. We use Monte Carlo simulation in the context of both theoretical and empirical populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights,...

This paper introduces a mixture model based on the beta distribution, without preestablished means and variances, to analyze a large set of Beauty-Contest data obtained from diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a better t of the experimental data, and more...

In this article we propose using small area estimators to improve the estimates of both the small and large area parameters. When the objective is to estimate parameters at both levels accurately, optimality is achieved by a mixed sample design of fixed and proportional allocations. In the mixed...

Structural equation models are widely used in economic, social and behavioral studies to analyze linear interrelationships among variables, some of which may be unobservable or subject to measurement error. Alternative estimation methods that exploit different distributional assumptions are now...

Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although...