Add to ORKGIn this paper I present a class of discrete choice models for ordinal response variables based on a generalization of the stereotype model. The stereotype model can be derived and generalized as a random utility model for ordered alternatives. Random utility models can be specified to account for heteroscedas-tic and correlated utilities. In the case of the generalized stereotype model this includes category-specific random effects due to individual differences in response style. But unlike standard random utility models the generalized stereotype model is better suited for ordinal response variables and can be interpreted as a kind of unidimensional unfolding model. This paper discusses the specification, interpretation, identifi-cation, a...
Traditional statistical models with random effects account for heterogeneity in the population with ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
When a binary or ordinal regression model incorrectly assumes that error variances are the same for ...
The collection and use of ordinal variables are common in many psychological and psychiatric studies...
Literature on the models for ordinal variables grew very fast in the last decades and several propos...
Literature on the models for ordinal variables grew very fast in the last decades and several propos...
Literature on the models for ordinal variables grew very fast in the last decades and several propos...
This paper presents two new model-based goodness-of-fit tests for the ordered stereotype model appli...
In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political ...
In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political ...
In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete Uniform ...
In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete Uniform ...
In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete Uniform ...
In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
When a binary or ordinal regression model incorrectly assumes that error variances are the same for ...
The collection and use of ordinal variables are common in many psychological and psychiatric studies...
Literature on the models for ordinal variables grew very fast in the last decades and several propos...
Literature on the models for ordinal variables grew very fast in the last decades and several propos...
Literature on the models for ordinal variables grew very fast in the last decades and several propos...
This paper presents two new model-based goodness-of-fit tests for the ordered stereotype model appli...
In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political ...
In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political ...
In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete Uniform ...
In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete Uniform ...
In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete Uniform ...
In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
Traditional statistical models with random effects account for heterogeneity in the population with ...
When a binary or ordinal regression model incorrectly assumes that error variances are the same for ...