This thesis considers a range of extensions through which heterogeneity can be included in ordered choice models, with the aim on increasing flexibility and ensuring models accurately represent the underlying data generating processes. In addition, this thesis includes discussion of variable choice in several highly relevant empirical applications including self-assessed health, tobacco consumption, and doctor utilisation. The thesis commences by offering a review of current techniques for allowing for heterogeneity. Each of the models discussed, as well as an extended model for unobserved heterogeneity, are estimated on data from the Household, Income and Labour Dynamics Survey of Australia. The second chapter investigates new extensions...
© William H. Greene and David A. Hensher 2010.It is increasingly common for analysts to seek out the...
Recent advances in "simulation based inference" have made it feasible to estimate discrete choice mo...
When a binary or ordinal regression model incorrectly assumes that error variances are the same for ...
This thesis considers a range of extensions through which heterogeneity can be included in ordered c...
Discrete variables that have an inherent sense of ordering across outcomes are commonly found in lar...
Discrete variables that have an inherent sense of ordering across outcomes are commonly found in lar...
Different voters behave differently at the polls, different students make different university choic...
This thesis consists of four essays on modelling and estimating unobserved consumer heterogeneity in...
Health services researchers are increasingly using discrete choice experiments (DCEs) to model a lat...
This paper investigates alternative methods to account for preference heterogeneity in choice experi...
Health services researchers are increasingly using discrete choice experiments (DCEs) to model a lat...
Recent advances in "simulation based inference" have made it feasible to estimate discrete choice mo...
A growing number of empirical studies involve the assessment of influences on a choice amongst order...
This paper examines the distribution of preferences in a sample of patients who responded to a disc...
Abstract. When a binary or ordinal regression model incorrectly assumes that error variances are the...
© William H. Greene and David A. Hensher 2010.It is increasingly common for analysts to seek out the...
Recent advances in "simulation based inference" have made it feasible to estimate discrete choice mo...
When a binary or ordinal regression model incorrectly assumes that error variances are the same for ...
This thesis considers a range of extensions through which heterogeneity can be included in ordered c...
Discrete variables that have an inherent sense of ordering across outcomes are commonly found in lar...
Discrete variables that have an inherent sense of ordering across outcomes are commonly found in lar...
Different voters behave differently at the polls, different students make different university choic...
This thesis consists of four essays on modelling and estimating unobserved consumer heterogeneity in...
Health services researchers are increasingly using discrete choice experiments (DCEs) to model a lat...
This paper investigates alternative methods to account for preference heterogeneity in choice experi...
Health services researchers are increasingly using discrete choice experiments (DCEs) to model a lat...
Recent advances in "simulation based inference" have made it feasible to estimate discrete choice mo...
A growing number of empirical studies involve the assessment of influences on a choice amongst order...
This paper examines the distribution of preferences in a sample of patients who responded to a disc...
Abstract. When a binary or ordinal regression model incorrectly assumes that error variances are the...
© William H. Greene and David A. Hensher 2010.It is increasingly common for analysts to seek out the...
Recent advances in "simulation based inference" have made it feasible to estimate discrete choice mo...
When a binary or ordinal regression model incorrectly assumes that error variances are the same for ...