Bonney, George E.Kötting, JoachimUrfer, Wolfgang2004-12-062004-12-061998http://hdl.handle.net/2003/483810.17877/DE290R-6817An importatnt aim in forest-ecosystem investigation is to analyse the development of forest damages and to quantify changes in the damage-states over time of individual trees by influential factors. In addition to the ordinal measurement in such longitudinal studies one has to consider spatial correlations of the trees within an ecosystem. We present a practical method to include such dependency structures using logistic regression models. The strategy is to adopt the disposition model for correlated binary data (Bonney (1998)) and extend it to an ordinal-disposition-transitional model (ODT-model). This includes proportional-odds-transitional model(POT-model) as a special case, assuming independence over time and space given a markov model of first order. The ODT-model is used to analyse dynamic changes of damage in forest-ecosystems. The analysed data was sampled with infrared aerial photos by the Swiss Federal Institute for Forest, Snow and Landsscpage Research(Forschungsanstalt Wald, Schnee und Landschaft (WSL))Switzerland. A acomparison of the independent case (POT-model) with the dependent case (ODT-model) shows that spatial correlations in forest ecosystem should not be neglected.enUniversitätsbibliothek DortmundCorrelated categorical observationDisposition modelForest-ecosystemInfrared aerial photosLongitudial dataOrdinal outcomeProportional-odds modelRegression modelspatial correlationtransitional model310report