Null hypothesis significance testing is the typical statistical approach in search of the truthfulness of hypotheses. This method does not formally consider the prior credence in the hypothesis, which affects the chances of reaching correct conclusions. When scientifically implausible or empirically weakly supported hypotheses are tested, there is an increased risk that a positive finding in a test in fact is false positive.
Alternative data-analysis techniques have been well-known among methodologists for decades but this knowledge, mainly collected in methods journals, seems to have had little impact on the practice of researchers to date. The main aim of this special issue is to introduce a collection of these alternative data-analysis methods in a nontechnical way, described by experts in the field.
Major national surveys, including the National Health Interview Survey (NHIS) and National Health and Nutrition Examination Survey (NHANES), have collected data on Americans’ use of complementary and alternative medicine. This page provides links to survey questions and results.