title: Diagnosing and dealing with multicollinearity.
abstract: The purpose of this article was to increase nurse researchers' awareness of the effects of collinear data in developing theoretical models for nursing practice. Collinear data distort the true value of the estimates generated from ordinary least-squares analysis. Theoretical models developed to provide the underpinnings of nursing practice need not be abandoned, however, because they fail to produce consistent estimates over repeated applications. It is also important to realize that multicollinearity is a data problem, not a problem associated with misspecification of a theorectical model. An investigator must first be aware of the problem, and then it is possible to develop an educated solution based on the degree of multicollinearity, theoretical considerations, and sources of error associated with alternative, biased, least-square regression techniques. Decisions based on theoretical and statistical considerations will further the development of theory-based nursing practice.
authors.affiliation: University of South Carolina College of Nursing, Columbia.
authors.forename: M A
authors.initials: MA
authors.lastname: Schroeder
mesh_terms: D006801:Humans; D008962:Models, Theoretical; D015999:Multivariate Analysis; D015399:Nursing Research; D009742:Nursing Theory; D012044:Regression Analysis; D015203:Reproducibility of Results