This paper proposes a robust estimator for a general class of linear latent variable models (GLLVM) (Moustaki and Knott 2000, Bartholomew and Knott 1999). It is based on a weighted score function that is simple to implement numerically and is made consistent using the basic idea of indirect...

In this paper we investigate the robustness properties of the class of minimum power divergence estimators for grouped data. This class contains the classical maximum likelihood estimators for grouped data. We find that the bias of these estimators due to deviations from the assumed underlying...

The aim of this investigation is to design a study which will take place in a particular hospital, to enquire if the recent breastfeeding campaign in this hospital has been successful. External sources and previous survey results are used to define the relevant features of the phenomena under...

Lorenz curves and associated tools for ranking income distributions are commonly estimated on the assumption that full, unbiased samples are available. However, it is common to find income and wealth distributions that are routinely censored or trimmed. We derive the sampling distribution for a...