Fitting Adjusted Limited Dependent Variable Mixture Models to EQ-5D

Tails from the Peak District: Adjusted Censored Mixture Models of EQ-5D Health State Utility Values

Health state utility data generated using the EQ-5D instrument are typically right bounded at one with a substantial gap to the next set of observations, left bounded by some negative value, and are multi modal. These features present challenges to the estimation of the e¤ect of clinical and socioeconomic characteristics on health utilities. We present an adjusted censored model and then use th...

The relationship between EQ-5D, HAQ and pain in patients with rheumatoid arthritis: further validation and development of the limited dependent variable, mixture model approach

Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets.

BACKGROUND A five-level version of the EuroQol five-dimensional (EQ-5D) descriptive system (EQ-5D-5L) has been developed, but value sets based on preferences directly elicited from representative general population samples are not yet available. The objective of this study was to develop values sets for the EQ-5D-5L by means of a mapping ("crosswalk") approach to the currently available three-l...

Estimating Contaminated Limited Dependent Variable Models

Smith for helpful comments and to Richard Blundell for kindly making his data available. In 1imi ted dependent variable models the estimators obtained by maximising the normal likelihood function are generally inconsistent when the assumption of normality ls falseo Arabmazar and Schmidt (1982) have shown that the bias trom non-normality can be substantial when the degree of censoring (or trunca...

On Fitting Mixture Models

Consider the problem of tting a nite Gaussian mixture, with an unknown number of components, to observed data. This paper proposes a new minimum description length (MDL) type criterion, termed MMDL (formixtureMDL), to select the number of components of the model. MMDL is based on the identi cation of an \equivalent sample size", for each component, which does not coincide with the full sample s...