Statistical procedures in clinical pharmacology: decision-theorectic foundations.
The function of statistical analysis is to reach optimal decisions in situations of principal uncertainty. The foundations of statistical procedures are experiments X, whose distributions PX are characterised by random samples. Within given classes of distributions (distribution hypothesis) mathematical statistics make optimal procedures available, which allow conclusions on the real properties of PX. The use of optimal procedures minimises the risk of incorrect decisions made on the basis of random samples (principle of greatest chance). Statistics, however, refrain from any statement on the quality of the decision to which a procedure in a certain situation leads. Against a decision-theoretic background of statistical decisions the growing complexity of clinical-pharmacological test models leads to the necessity of using descriptive-statistical methods on an even larger scale. The aim should be to reduce the number of individual parameters to a few important factors, so that the relation between the number of trial subjects on the one hand and the number of parameters on the other remains valid for meaningful statistical statements.
D002986:Clinical Trials as Topic; D003657:Decision Making; D010601:Pharmacology, Clinical; D013223:Statistics as Topic