Literature DB >> 7973242

Alternative models for ordinal logistic regression.

S Greenland1.   

Abstract

Armstrong and Sloan have reviewed two types of ordinal logistic models for epidemiologic data: the cumulative-odds model and the continuation-ratio model. I review here certain aspects of these models not emphasized previously, and describe a third type, the stereotype model, which in certain situations offers greater flexibility coupled with interpretational advantages. I illustrate the models in an analysis of pneumoconiosis among coal miners.

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Year:  1994        PMID: 7973242     DOI: 10.1002/sim.4780131607

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  14 in total

1.  [Relation between certain diseases and frequency of depression in geriatric patients].

Authors:  V Zietemann; P Zietemann; R Weitkunat; A Kwetkat
Journal:  Nervenarzt       Date:  2007-06       Impact factor: 1.214

2.  Missing exposure data in stereotype regression model: application to matched case-control study with disease subclassification.

Authors:  Jaeil Ahn; Bhramar Mukherjee; Stephen B Gruber; Samiran Sinha
Journal:  Biometrics       Date:  2010-06-16       Impact factor: 2.571

3.  Dose-finding clinical trial design for ordinal toxicity grades using the continuation ratio model: an extension of the continual reassessment method.

Authors:  Emily M Van Meter; Elizabeth Garrett-Mayer; Dipankar Bandyopadhyay
Journal:  Clin Trials       Date:  2012-04-30       Impact factor: 2.486

4.  L1 penalized continuation ratio models for ordinal response prediction using high-dimensional datasets.

Authors:  K J Archer; A A A Williams
Journal:  Stat Med       Date:  2012-02-23       Impact factor: 2.373

5.  Assigning scores for ordered categorical responses.

Authors:  Daniel Fernández; Ivy Liu; Roy Costilla; Peter Yongqi Gu
Journal:  J Appl Stat       Date:  2019-10-09       Impact factor: 1.416

6.  The trend odds model for ordinal data.

Authors:  Ana W Capuano; Jeffrey D Dawson
Journal:  Stat Med       Date:  2012-12-06       Impact factor: 2.373

7.  Bayesian inference for the stereotype regression model: Application to a case-control study of prostate cancer.

Authors:  Jaeil Ahn; Bhramar Mukherjee; Mousumi Banerjee; Kathleen A Cooney
Journal:  Stat Med       Date:  2009-11-10       Impact factor: 2.373

8.  Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh.

Authors:  Sumonkanti Das; Rajwanur M Rahman
Journal:  Nutr J       Date:  2011-11-14       Impact factor: 3.271

9.  A comparison of ordinal regression models in an analysis of factors associated with periodontal disease.

Authors:  Shivalingappa B Javali; Parameshwar V Pandit
Journal:  J Indian Soc Periodontol       Date:  2010-07

10.  Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time.

Authors:  Rose D Baker; Christian Weinand; James C Jeng; Henk Hoeksema; Stan Monstrey; Sarah A Pape; Robert Spence; David Wilson
Journal:  BMC Med Res Methodol       Date:  2009-02-16       Impact factor: 4.615

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