For testing one-sided but also two-sided hypotheses concerning several treatment arms in group sequentially performed clinical trials with arbitrary outcome variables, a general learning method is considered that allows for a complete self-designing of the study. All information available prior...

A class of self-designing clinical trials is considered which according to an effective but simple, finite learning algorithm consists of automatically adaptively planned weighted group sequential trials with a decision about rejection of the null-hypothesis at each step, but the full...

In a general variance component model with positive variance components a short-cut method is presented that yields almost everywhere for these components positive estimators that are invariant with respect to mean value translation and stay near the unbiasedness.

In combining several tests of significance the individual test statistics are allowed to be dependent. By choosing the weighted inverse normal method for the combination, the dependency of the original test statistics is then characterized by a correlation of the transformed statistics. For this...

Sind in einer statistischen Analyse mehr als eine Variationsursache zu berücksichtigen_ so zerfällt die Gesamtvariation in mehrere Komponenten. Für diese sind in der Regel auch Beziehungen oder Ordnungen bekannt. Aber keine der bekannten Schätztheorien ist in der Lage, diese Ordnungen auch...

In many fields of applications, test statistics are obtained by combining estimates from several experiments, studies or centres of a multicentre trial. The commonly used test procedure to judge the evidence of a common overall effect can result in a considerable overestimation of the...

Positive estimators of the between-group (between-study) variance are proposed. Explicit variance formulae for the estimators are given and approximate confidence intervals for the between-group variance are constructed, as our proposal to a long outstanding problem. By Monte Carlo simulation,...