title: [Identification of types in small samples with the help of bootstrap simulation (illustrated with the help of the anxiety/depression subscales of the HAD)].
abstract: Using a HAD-file as an illustration, we could show that small files (n = 50) can provide statistically significant results if we apply bootstrap simulation. First the subscales "anxiety" and "depression" are computed and afterwards classified (in three categories). Both classified subscales are cross tabled and submitted to a configurational cluster analysis. One type can be clearly identified. To test the stability of the one-type solution, a bootstrap simulation (Lautsch/von Weber: BOOTSTRAP) is applied. The simulation confirms the one-type solution.
authors.affiliation: Universität Kassel. erla@hrz.uni-kassel.de
authors.forename: E
authors.initials: E
authors.lastname: Lautsch
authors.forename: L
authors.initials: L
authors.lastname: Schiltz
mesh_terms: D001007:Anxiety / Q000145:classification*; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D003863:Depression / Q000145:classification*; D006801:Humans; D011581:Psychological Tests; D018401:Sample Size