Goodness of Link Tests for Binary Response Data

  • Yeo, In-Kwon (Department of Control and Instrumentation Engineering, Kangwon National University)
  • Published : 2001.08.01

Abstract

The present paper develops a method to check the propriety of link functions for binary data. In order to parameterize a certain type of goodness of the link, a family of link functions indexed by a shape parameter is proposed. I first investigate the maximum likelihood estimation of the shape parameter as well as regression parameters and then derive their large sample behaviors of the estimators. A score test is considered to evaluate the goodness of the current link function. For illustration, I employ two families of power transformations, the modulus transformation by John and Draper (1980) and the extended power transformation by Yeo and Johnson (2000), which are appropriate to detect symmetric and asymmetric inadequacy of the selected link function. respectively.

Keywords

References

  1. Biometrika v.68 On two families of transformations to additivity for binary response data Aranda Ordaz,F.J.
  2. Biometrika v.52 Locally asymptotically most stringent tests and Lagrangian multiplier tests of linear hypotheses Bhat,B.R.;Nagnur,B.N.
  3. Annals of Applied Biology v.22 The calculation of the dosage-mortality curve Bliss,C.J.
  4. Journal of the American Statistical Association v.89 Testing goodness of fit for a parametric family of link functions Cheng,K.F.;Wu,J.W.
  5. Analysis of Binary Data(2nd Ed.) Cox,D.R.;Snell,E.J.
  6. Biometrika v.69 Use of the Box-Cox transformation with binary response models Guerrero,V.M.;Johnson,R.A.
  7. Applied Statistics v.29 An alternative family of transformations John,J.A.;Draper,N.R.
  8. Human Biology v.38 Age at menarche in Warsaw girls in 1965 Milicer,H.;Szczotka,F.
  9. Applied Statistics v.29 Goodness of link tests for generalized linear models Pregibon,D.
  10. Biometric v.32 Generalization of the probit and logit methods for dose response curves Prentice,R.L.
  11. Annals of Mathematical Statistics v.27 Uniform convergence of random functions with applications to statistics Rubin,H.
  12. Journal of the American Statistical Association v.83 Generalized logistic models Stukel,T.A.
  13. Journal of the American Statistical Association v.86 A lack-of-fit test for the mean function in a generalized linear model Su,J.Q.;Wei,L.J.
  14. Biometrika v.61 Qausi-likelihood functions, generalized linear models, and the Gaussian-Newton method Wedderburn,R.W.M.
  15. Econometrica v.50 Maximum likelihood estimation of misspecified models White,H.
  16. Journal of the Korean Statistical Society v.27 The generalized logistic models with transformations Yeo,I.K.;Johnson,R.A.
  17. Biometrika v.87 A new family of power transformations to improve normality or symmetry Yeo,I.K.;Johnson,R.A.