A unified framework for the comparison of treatments with ordinal responses
From MaRDI portal
Publication:487599
DOI10.1007/s11336-013-9367-8zbMath1303.62105OpenAlexW2046205578WikidataQ43449421 ScholiaQ43449421MaRDI QIDQ487599
Wai-Yin Poon, Tong-Yu Lu, Siu Hung Cheung
Publication date: 22 January 2015
Published in: Psychometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11336-013-9367-8
Related Items
Multiple comparisons of treatments with skewed ordinal responses, Ordinal probability effect measures for group comparisons in multinomial cumulative link models
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Comparing several exponential populations with more than one control
- Analysis of structural equation model with ignorable missing continuous and polytomous data
- Bayesian analysis of multivariate probit models with surrogate outcome data
- Ordinal data, ordered scale points, and order statistics
- A note on comparing the estimates of models for cluster-correlated or longitudinal data with binary or ordinal outcomes
- A latent variable model for discrete multivariate psychometric waiting times
- A hierarchical Bayesian statistical framework for response time distributions
- A joint modeling approach for reaction time and accuracy in psycholinguistic experiments
- Assessing Toxicities in a Clinical Trial: Bayesian Inference for Ordinal Data Nested within Categories
- THE GENERALIZATION OF PROBIT ANALYSIS TO THE CASE OF MULTIPLE RESPONSES
- Partial Proportional Odds Models for Ordinal Response Variables
- Regression, Discrimination and Measurement Models for Ordered Categorical Variables
- Inferences for the Two-Parameter Exponential Distribution Under Type I Censored Sampling
- Latent Variable Models for Clustered Ordinal Data
- Dose-Finding Based on Multiple Toxicities in a Soft Tissue Sarcoma Trial
- Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis
- On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
