English, Article, Journal or magazine article edition: Semiparametric generalized linear models Paul Rathouz

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Bookmark: http://trove.nla.gov.au/version/176336
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Semiparametric generalized linear models
Author
  • Paul Rathouz
Physical Description
  • preprint
Notes
  • I propose a new class of generalized linear models. As with the existing models, these new models are specified via a linear predictor and a link function for the mean of response Y as a function of predictors X. However, here, the “baseline” distribution of Y when the linear predictor is zero is left unspecified and is estimated from the data. The response distribution when the linear predictor differs from zero is then generated via exponential tilting of the baseline distribution, yielding a response model that is a member of the natural exponential family, with corresponding canonical link and variance functions. The resulting model has a similar level of flexibility as the proportional odds model. Maximum likelihood estimators are developed for response distribution with finite support, and the new model is studied and illustrated through simulations and example analyses from aging and psychiatry research.
  • RePEc:boc:nsug08:15
Language
  • English
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