Multidimensional scaling (MDS) is an exploratory technique used to identify unrecognized dimensions affecting behavior. Using MDS reduces large amounts of data to relatively simple, easy-to-visualize structures that reveal important relationships in an economical way and provides general solutions to many problems in perception, emotion, and cognition, where the stimuli are too complex to be quantified by other means.
To provide a basic introduction to MDS for the nonmathematician, in particular, the spatial distance model, which maps objects as points in a multidimensional space.
This introductory article is focused on the spatial distance model, which is used to map objects as points in a multidimensional space. A brief overview of MDS is provided, the procedure is outlined with examples, and nursing implications are discussed.
Individual and aggregate analyses and individual differences scaling results are presented.
Using MDS is ideal for the study of such complicated issues as a patient's perception of cancer pain, breathlessness in individuals with chronic obstructive pulmonary disease, and the assessment of vulnerable populations where social desirability bias is an issue.
Marie E. Mugavin, PhD, RN, is Assistant Professor, College of Nursing, Health Sciences Center, University of New Mexico, Albuquerque.
Accepted for publication August 24, 2007.
Corresponding author: Marie E. Mugavin, PhD, RN, College of Nursing, Health Sciences Center, University of New Mexico, MSC09 5350, 1 University of New Mexico, Albuquerque, NM 87131-0001 (e-mail: Memugavin@salud.unm.edu).