A Bayesian analysis of bivariate ordinal data: Wisconsin epidemiologic study of diabetic retinopathy revisited

Keywords

Bivariate analysis, Bayesian probability, Computer science, Ordinal data, Data set

References

• Regression Models for Ordinal DataPeter McCullagh — 1980
• The analysis of binary dataR. L. Plackett, D. R. Cox — 1971
• Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACVFangyu Gao, Ronald Klein, Ronald Klein — 2000
• Prevalence of diabetes mellitus in southern Wisconsin.Ronald Klein, Ronald Klein, Scot E. Moss — 1984
• Analyzing bivariate ordinal data using a global odds ratioJohn Williamson, KyungMann Kim, Stuart R. Lipsitz — 1995
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesStuart Geman, Donald Geman — 1984
• Smoothing spline ANOVA for exponential families, with application to the Wisconsin Epidemiological Study of Diabetic Retinopathy : the 1994 Neyman Memorial LectureGrace Wahba, Yuedong Wang, Chong Gu — 1995
• Marginal Likelihood from the Gibbs OutputSiddhartha Chib — 1995
• Using smoothing spline anova to examine the relation of risk factors to the incidence and progression of diabetic retinopathy.Yuedong Wang, Grace Wahba, Chong Gu — 1997
• Computing Bayes Factors by Combining Simulation and Asymptotic ApproximationsThomas J. DiCiccio, Robert E. Kass, Adrian E. Raftery — 1997
• GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data.John Williamson, Stuart R. Lipsitz, Kyung Mann Kim — 1999
• The Wisconsin epidemiologic study of diabetic retinopathy. II. Prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years.Ronald Klein — 1984
• Illustration of Bayesian Inference in Normal Data Models Using Gibbs SamplingAlan E. Gelfand, Susan E. Hills, Amy Racine-Poon — 1990
• A global odds ratio regression model for bivariate ordered categorical data from ophthalmologic studies.John Williamson, KYUNGMANN KIM — 1996
• Global cross-ratio models for bivariate, discrete, ordered responses.Jocelyn R. Dale — 1986
• Smoothing Spline ANOVA for Multivariate Bernoulli Observations With Application to Ophthalmology DataFangyu Gao, Grace Wahba, Ronald Klein — 2001
• On the use of a working correlation matrix in using generalised linear models for repeated measuresMartin Crowder — 1995
• Marginal Modeling of Correlated Ordinal Data Using a Multivariate Plackett DistributionGeert Molenberghs, Emmanuel Lesaffre — 1994
• An annotated bibliography of methods for analysing correlated categorical data.M. L. N. Ashby, John Neuhaus, Walter W. Hauck — 1992
• Inference from Iterative Simulation Using Multiple SequencesAndrew Gelman, Donald B. Rubin — 1992

Cited by

• A Latent Mixture Approach to Modeling Zero-Inflated Bivariate Ordinal DataRajendra Kadel — 2013
• Modeling Ordered Choices: A PrimerWilliam H. Greene, David A. Hensher — 2010
• Simultaneous causality between health status and employment status within the population aged 30-59 in FranceThomas Barnay, François Legendre — 2012
• Modeling Ordered Choices: A Primer and Recent DevelopmentsWilliam H. Greene, David A. Hensher — 2008
• Joint Models and Their ApplicationsYangxin Huang, Lang Wu, Grace Y. Yi — 2012
• Bayesian Approach to Zero-Inflated Bivariate Ordered Probit Regression Model, with an Application to Tobacco UseShiferaw Gurmu, Getachew Dagne — 2012
• Bivariate versus univariate ordinal categorical data with reference to an ophthalmologic studyJean‐François Angers, Atanu Biswas — 2008
• Bayesian statistics in medicine: a 25 year reviewDeborah Ashby — 2006
• A latent variable regression model for asymmetric bivariate ordered categorical dataFarid Zayeri, Anoshirvan Kazemnejad — 2006
• The analysis of ordered categorical data: An overview and a survey of recent developmentsIvy Liu, Alan Agresti — 2005
• Bivariate cumulative probit model for the comparison of neuronal encoding hypothesesJulia Hillmann, Thomas Kneib, Lena Koepcke — 2014
• Hypothesis Testing Problems in an Unbalanced Longitudinal Ophthalmology StudyJonghyeon Kim — 2006
• A Bayesian analysis of the 4‐year follow‐up data of the Wisconsin epidemiologic study of diabetic retinopathyJean‐François Angers, Atanu Biswas — 2004
• Bayesian nonparametric multivariate ordinal regressionJunshu Bao, Timothy Hanson — 2015
• Bayesian Approach to Zero-Inflated Ordered Probit Models, with an Application ∗Shiferaw Gurmu, Getachew Dagne — 2009
• Prevalence and Risk Factors of Diabetic Retinopathy in Yazd ProvinceM. Dehghan, Marzieh Katibeh, Hamid Ahmadieh — 2013
• A Bayesian analysis of bivariate ordered categorical responses using a latent variable regression model: Application to diabetic retinopathy dataAnoshirvan Kazemnejad, Farid Zayeri, Nor Aishah Hamzah — 2010
• Determining the Prevalence of Retinopathy and Its Related Factors among Patients with Type 2 Diabetes in Kerman, IranŘeža Valizadeh, Mahmood Moosazadeh, Kambiz Bahaadini — 2016
• Modeling Paired Ordinal Response DataAnoshiravan Kazemnejad, Farid Zayeri — 2004
• THE PREVALENCE AND RELATED FACTORS OF DIABETIC NEPHROPATHY IN SHAHROUDEhsan Nezakati, Sohrabi Mohammad Bagher, Zolfaghari Pooneh — 2015

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