| Summary (2008) | |||||||||||||||||
Abstract | |||||||||||||||||
| This paper discusses marginal regression for repeated ordinal measurements that are isotonic over time. Such data are often observed in longitudinal studies on healing processes where, due to recovery, the status of patients only improves or stays the same. We showhow this prior information can be used to construct appropriate and parsimoniously parametrized marginal models. As a second as-pect, we also incorporate nonparametric tting of covariate e ects via a penalized quasi-likelihood or GEE approach. We illustrate our methods by an application to injuries from sporting activities. | |||||||||||||||||
Details der Publikation | |||||||||||||||||
| |||||||||||||||||