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A model for a multivariate binary response with covariates based on compatible conditionally specified logistic regressions

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  • Joe, Harry
  • Liu, Ying

Abstract

A model for a multivariate binary response vector with covariates is obtained. The conditional distribution of each binary response given the other binary responses and the covariates is equivalent to a logistic regression. A simple condition on the regression parameters is necessary and sufficient for the conditional distributions to be compatible, that is, yield a multivariate distribution for the binary response vector. The multivariate model has a wide range of dependence structure for the binary response variables, so it is more generally applicable compared with previous conditional models. The model is applied to a data set from cardiac surgery.

Suggested Citation

  • Joe, Harry & Liu, Ying, 1996. "A model for a multivariate binary response with covariates based on compatible conditionally specified logistic regressions," Statistics & Probability Letters, Elsevier, vol. 31(2), pages 113-120, December.
    • Handle: RePEc:eee:stapro:v:31:y:1996:i:2:p:113-120
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    Cited by:

    1. Carolyn J. Anderson & Jay Verkuilen & Buddy L. Peyton, 2010. "Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models," Journal of Educational and Behavioral Statistics, , vol. 35(4), pages 422-452, August.
    2. Carolyn Anderson, 2013. "Multidimensional Item Response Theory Models with Collateral Information as Poisson Regression Models," Journal of Classification, Springer;The Classification Society, vol. 30(2), pages 276-303, July.
    3. Garcia-Zattera, Maria Jose & Jara, Alejandro & Lesaffre, Emmanuel & Declerck, Dominique, 2007. "Conditional independence of multivariate binary data with an application in caries research," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3223-3234, March.
    4. Pei Wang & Dennis L. Chao & Li Hsu, 2011. "Learning Oncogenic Pathways from Binary Genomic Instability Data," Biometrics, The International Biometric Society, vol. 67(1), pages 164-173, March.
    5. repec:jss:jstsof:20:i06 is not listed on IDEAS

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