Continuing evolution of statistical tests in medical research

Abstract

The role of statistics in medical research starts at the planning stage of a clinical trial or laboratory experiment to establish the design and size of an experiment that will ensure a good prospect of detecting effects of clinical or scientific interest. Statistics is again used during data analysis (sample data) to make inferences valid in a wider population. In simple situations, computation of simple quantities such as P-values, confidence intervals, standard deviations, standard errors or application of some standard parametric or nonparametric tests may suffice. Moreover, despite the wide use of statistics in medical research, simple notions are sometimes misunderstood or misinterpreted by medical research workers, who have only a limited knowledge of statistics. This article, written for non-statisticians, is to explain what are the most common statistical tests used today in the field of medical research, tracing the evolution of statistical tests over time, in particular the introduction of nonparametric methods and, more recently, the NonParametric Combination (NPC) methodology. At the same time, this work seeks to identify some of the errors associated with their use, that often lead to an incorrect assessment and interpretation of results of medical research.