Modeling longitudinal data with ordinal response by varying coefficients

The paper presents a smooth regression model for ordinal data with
longitudinal dependence structure. A marginal model with cumulative
logit link (McCullagh 1980) is applied to cope for 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. A data example
demonstrates the exploratory flavor of the smooth model. In a
second step, the longitudinal dependence of the observations is
considered. Cumulative log odds ratios are fitted locally which
provides insight how the dependence of the ordinal observations
changes with time.