The goal of the research that lead to this paper was chiefly to examine the proportional odds model (McCullagh, 1980)—how it fits and how it predicts. This model can be seen below in (1). It is used to model categorical response data when the response categories have a natural ordering. Let J be the number of response categories. Let Y be the random respons
This investigation researches statistical methods for analysing ordered categorical data. Some stand...
Ordinal categorical random variables are random variables which take on values from a finite ordered...
Linear scoring coupled with parametric regression or ANOVA often is used to analyze responses measur...
This research was supported by the Undergraduate Research Opportunities Program (UROP)
The proportional odds model provides a powerful tool for analysing ordered categorical data and sett...
Proportional odds model examining the impact of seeing uncertainty in the initial recommendation on ...
Proportional odds model examining the impact of seeing uncertainty in the initial recommendation on ...
The proportional odds model (POM) is the most widely used model when the response has ordered catego...
<p>Results of the proportional odds model using position as response eight ordered categories.</p
The proportional odds model is commonly used in regression analysis to predict the outcome for an or...
In multi-category response models categories are often ordered. In case of ordinal response models, ...
The choice of the number m of response categories is a crucial issue in categorization of a continuo...
Kauermann G, Tutz G. Semi- and nonparametric modeling of ordinal data. JOURNAL OF COMPUTATIONAL AND ...
one of the most commonly used models for the analysis of ordinal categorical data an
In multi-category response models categories are often ordered. In case of ordinal response models, ...
This investigation researches statistical methods for analysing ordered categorical data. Some stand...
Ordinal categorical random variables are random variables which take on values from a finite ordered...
Linear scoring coupled with parametric regression or ANOVA often is used to analyze responses measur...
This research was supported by the Undergraduate Research Opportunities Program (UROP)
The proportional odds model provides a powerful tool for analysing ordered categorical data and sett...
Proportional odds model examining the impact of seeing uncertainty in the initial recommendation on ...
Proportional odds model examining the impact of seeing uncertainty in the initial recommendation on ...
The proportional odds model (POM) is the most widely used model when the response has ordered catego...
<p>Results of the proportional odds model using position as response eight ordered categories.</p
The proportional odds model is commonly used in regression analysis to predict the outcome for an or...
In multi-category response models categories are often ordered. In case of ordinal response models, ...
The choice of the number m of response categories is a crucial issue in categorization of a continuo...
Kauermann G, Tutz G. Semi- and nonparametric modeling of ordinal data. JOURNAL OF COMPUTATIONAL AND ...
one of the most commonly used models for the analysis of ordinal categorical data an
In multi-category response models categories are often ordered. In case of ordinal response models, ...
This investigation researches statistical methods for analysing ordered categorical data. Some stand...
Ordinal categorical random variables are random variables which take on values from a finite ordered...
Linear scoring coupled with parametric regression or ANOVA often is used to analyze responses measur...