Testing the proportional odds assumption in multiply imputed ordinal longitudinal data
From MaRDI portal
Publication:5130336
DOI10.1080/02664763.2015.1023704OpenAlexW1978590959MaRDI QIDQ5130336
No author found.
Publication date: 4 November 2020
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2015.1023704
clinical trialsmissing datacategorical outcomemultivariate normal imputationlongitudinal analysisproportional odds assumptionordinal imputation model
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Longitudinal data analysis using generalized linear models
- Some simple methods for generating correlated categorical variates
- On the existence of maximum likelihood estimates in logistic regression models
- Hypothesis testing of regression parameters in semiparametric generalized linear models for cluster correlated data
- Partial Proportional Odds Models for Ordinal Response Variables
- The Calculation of Posterior Distributions by Data Augmentation
- A Tutorial on the SWEEP Operator
- Inference and missing data
- Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
- Semiparametric Efficiency in Multivariate Regression Models with Missing Data
- Modeling the Drop-Out Mechanism in Repeated-Measures Studies
- A Simulation Study Comparing Multiple Imputation Methods for Incomplete Longitudinal Ordinal Data
- Multiple imputation of discrete and continuous data by fully conditional specification
- Estimation of the probability of an event as a function of several independent variables
This page was built for publication: Testing the proportional odds assumption in multiply imputed ordinal longitudinal data