We review statistical methods for analysing healthcare resource use and costs, their ability
to address skewness, excess zeros, multimodality and heavy right tails, and their ease for …

Background: Anxiety is associated with decreased functioning and quality of life. It may have
added importance in diabetes for its potential adverse effects on regimen adherence and …

The first edition of Applied Health Economics did an expert job of showing how the
availability of large scale data sets and the rapid advancement of advanced econometric …

Mixed linear regression involves the recovery of two (or more) unknown vectors from
unlabeled linear measurements; that is, where each sample comes from exactly one of the …

In this paper, a conditional demand function is estimated for the length of stay at a tourist
destination. The microeconomic model specifies the demand for the length of stay …

OBJECTIVE: To measure and explain income-related inequalities in health and health care
utilization in the period 2000-2009 in Chile, while assessing variations within the country …

In this paper, we study the mixed linear regression (MLR) problem, where the goal is to
recover multiple underlying linear models from their unlabeled linear measurements. We …

Using three waves of data from the European Community Household Panel this paper
estimates demand for physician services equations for 12 European Countries. We focus on …

Usual econometric (least squares) methods will yield less precise estimates of means and
marginal effects. If failing to deal with inherently nonlinear response may lead to biased …

We consider the problem of solving mixed random linear equations with $ k $ components.
This is the noiseless setting of mixed linear regression. The goal is to estimate multiple …