Interpreting “statistical hypothesis testing” results in clinical research.

ABSTRACT

Difference between “Clinical Signifi cance and Statistical Signifi cance” should be kept in mind while interpreting “statistical hypothesis testing” results in clinical research. This fact is already known to many but again pointed out here as philosophy of “statistical hypothesis testing” is sometimes unnecessarily criticized mainly due to failure in considering such distinction. Randomized controlled trials are also wrongly criticized similarly. Some scientifi c method may not be applicable in some peculiar/particular situation does not mean that the method is useless. Also remember that “statistical hypothesis testing” is not for decision making and the fi eld of “decision analysis” is very much an integral part of science of statistics. It is not correct to say that “confi dence intervals have nothing to do with confi dence” unless one understands meaning of the word “confi dence” as used in context of confi dence interval. Interpretation of the results of every study should always consider all possible alternative explanations like chance, bias, and confounding. Statistical tests in inferential statistics are, in general, designed to answer the question “How likely is the difference found in random sample(s) is due to chance” and therefore limitation of relying only on statistical signifi cance in making clinical decisions should be avoided.