Modeling longitudinal data with ordinal response by varying coefficients.
This paper presents a smooth regression model for ordinal data with longitudinal dependence structure. A marginal model with cumulative logit link is applied to cope with the ordinal scale and the main and covariate effects in the model are allowed to vary with time. Local fitting is pursued and asymptotic properties of the estimates are discussed. In a second step, the longitudinal dependence of the observations is considered. Cumulative log odds ratios are fitted locally, which allows investigation of how the longitudinal dependence of the ordinal observations changes with time.
Kauermann
G
G
Ludwig-Maximilians-University Munich, Institute for Statistics, Germany. kauerman@stat.uni-muenchen.de
D001699:Biometry / Q000379:methods; D005500:Follow-Up Studies; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D015337:Multicenter Studies as Topic; D016011:Normal Distribution; D016017:Odds Ratio; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011878:Radiotherapy / Q000009:adverse effects*; D012044:Regression Analysis; D018709:Statistics, Nonparametric