Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Location-scale cumulative odds models for ordinal data: a generalized non-linear model approach

C Cox1

  • 1Department of Biostatistics, University of Rochester, School of Medicine and Dentistry, New York 14642, USA.

Statistics in Medicine
|June 15, 1995
PubMed
Summary

This study synthesizes and generalizes proportional odds regression models for ordered categories. It extends existing models to include scale and location parameters, enhancing their application in ROC analysis and statistical modeling.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Learning curves and breast cancer lymphatic mapping: institutional volume index.

The Journal of surgical research·2001
Same author

Encephalopathy associated with respiratory syncytial virus bronchiolitis.

Journal of child neurology·2001
Same author

Incidental discovery of pelvic cholelithiasis on diagnostic laparoscopy.

Surgical endoscopy·2001
Same author

Methylmercury and neurodevelopment: reanalysis of the Seychelles Child Development Study outcomes at 66 months of age.

JAMA·2001
Same author

Depression and self-reported functional status in older primary care patients.

The American journal of psychiatry·2001
Same author

A randomized, controlled trial of remacemide for motor fluctuations in Parkinson's disease.

Neurology·2001

Area of Science:

  • Statistics
  • Biostatistics
  • Statistical Modeling

Background:

  • Proportional odds regression models are used for ordered categorical data.
  • Existing generalizations include models with scale/location parameters for ROC analysis and partial proportional odds models.

Purpose of the Study:

  • To synthesize and generalize two existing families of proportional odds regression models.
  • To explore the properties of this extended family of models through examples.

Main Methods:

  • The study proposes an extended family of proportional odds models.
  • It emphasizes the computation of maximum likelihood estimates, asymptotic standard deviations, and goodness-of-fit statistics.
  • Non-linear regression programs in standard statistical software (e.g., SAS) are utilized.

Related Experiment Videos

Main Results:

  • The paper discusses and illustrates the properties of the synthesized and generalized models.
  • The methods allow for the estimation of parameters and assessment of model fit.

Conclusions:

  • The extended family of models offers a flexible framework for analyzing ordered categorical data.
  • The proposed computational methods are practical for implementation in standard statistical software.