Partial residuals in cumulative regression models for ordinal data
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We are concerned with cumulative regression models for an ordered categorical response variable Y. We propose two methods to build partial residuals from regression on a subset Z1 of covariates Z., which take into regard the ordinal character of the response. The first method makes use of a multivariate GLM-representation of the model and produces residual measures for diagnostic purposes. The second uses a latent continuous variable model and yields new (adjusted) ordinal data Y*. Both methods are illustrated by a data set from forestry.
Key wordsOrdered categorical data generalized linear model cumulative regression model latent continuous variable model partial residuals trend removal forest damage data
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- Göttlein, A. & Pruscha, H. (1992). Ordinal time series models with application to forest damage data. In: Lecture Notes in Statistics 78, Springer, N.Y., 113–118.Google Scholar