Kauermann, G. (2000). Modeling longitudinal data with ordinal response by varying coefficients. Biometrics 56, 692--698. Home/Search Document Details and Download
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Marginal Regression Models with Varying Coefficients for.. - Gieger (Correct)
....be used to estimate additive models for correlated responses. Semiparametric modeling of predictors in estimating equations based on local regression techniques has recently been considered by Carroll, Ruppert and Welsh (1998) and more speci cally for longitudinal data with ordinal responses by Kauermann (1999). Fahrmeir, Gieger and Heumann (1999) discussed semiparametric marginal modeling of dependent ordinal responses by penalty approaches in the context of a clinical study. They showed how the model which we present here in detail can be adapted to situations with an isotonic response pattern. ....
KAUERMANN G. (1999). Modeling Longitudinal Data with Ordinal Response by Varying Coecients. Forthcoming in Biometrics.
Semiparametric Modeling of Ordinal Data - Kauermann, Tutz (2000) Self-citation (Kauermann) (Correct)
.... pursue a local and pro le likelihood approach which extends smooth estimation as considered in semiparametric models (see also Severini Wong, 1992) Cumulative models for dependent ordinal data are treated in Fahrmeir Pritscher (1996) or Heagerty Zeger (1996) in a parametric fashion and in Kauermann (1999) using nonparametric components. The latter paper does 4 not make use of the semiparametric approaches, which are investigated here. 2 The Cumulative Model 2.1 Varying Coecient Model Although model (3) is already a semiparametric model, we consider a more general form of (3) This is done by ....
Kauermann, G. (1999). Modeling longitudinal data with ordinal response by varying coecients. Biometrics, (to appear).
Modeling Migraine Severity With Autoregressive Ordered.. - Claudia Czado Anette (Correct)
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Kauermann, G. (2000). Modeling longitudinal data with ordinal response by varying coefficients. Biometrics 56, 692--698.
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