Regression analyses
chronic disease
REGRESSION, CHRONIC DISEASE
For the U10, U11 and J2, regression models show that participation in the examinations has the strongest influence on detecting a diagnosis among the included variables. The presence of a chronic disease and sex - for the U10 and U11 males and for the J2 females - also tend to more often predict the detection of a diagnosis. The model for the U10 further shows that German nationality and unemployment have a significant effect. In the model for the U11, German nationality, unemployment and living in a semi-rural region are associated with detecting a diagnosis (see Table 
Binominal logistic regression analyses for diagnosis within U10, U11 and J2 examinations (H

Binominal logistic regression analyses for treatment initiation (H
