The Importance of Attending to Underlying Statistical Assumptions

Statistical tools are delicate instruments. When used properly, they help quantitative researchers illuminate relationships important to both practitioners and theorists; when used carelessly, they can bring about unjustified, distorted, and/or misleading claims. Almost every statistical tool has underlying assumptions (ie, prerequisite conditions) that supposedly govern its use. In this article, four questions concerning such assumptions are raised: What is an underlying statistical assumption? What are the consequences, if any, of violating them? Do applied researchers (and particularly those who publish articles in Newborn and Infant Nursing Reviews) pay attention to the assumptions that underlie the statistical procedures they use? What new insights into statistical assumptions have come about during the last 10 to 15 years?