Longitudinal designs are indispensable to the study of change in outcomes over time and have an important role in health, social, and behavioral sciences. However, these designs present statistical challenges particularly related to accounting for the variance and covariance of the repeated measurements on the same participants and to modeling outcomes that are not normally distributed.
The purpose of this study was to introduce a general methodology for longitudinal designs to address these statistical challenges and to present an example of an analysis conducted with data collected in a randomized clinical trial. In this example, the outcome of interest-monthly health-related out-of-pocket expenses incurred by breast cancer survivors-had a skewed distribution.
Common statistical approaches are for longitudinal analysis using linear and generalized linear mixed models are reviewed, and the discussed methods are applied to analyze monthly health-related out-of-pocket expenses.
Although standard statistical software is available to conduct longitudinal analyses, training is necessary to understand and to take advantage of the various options available for model fitting. However, knowledge of the basics of the methodology allows assimilation and incorporation into practice of evidence from the numerous studies that use these designs.
Andres Azuero, PhD, MBA, is Assistant Professor and Biostatistician, School of Nursing, University of Alabama at Birmingham.
Maria Pisu, PhD, is Assistant Professor, Division of Preventive Medicine, School of Medicine, University of Alabama at Birmingham.
Patrick McNees, PhD, FAAN, is Professor, School of Nursing and Associate Dean for Research, School of Health Professions, University of Alabama at Birmingham.
Jeffrey Burkhardt, PhD, is Professor, School of Health Professions, University of Alabama at Birmingham.
Rachel Benz, BSN, RN, is Research Assistant, School of Nursing, University of Alabama at Birmingham.
Karen Meneses, PhD, RN, FAAN, is Professor and Associate Dean for Research, School of Nursing, University of Alabama at Birmingham.
Accepted for publication March 8, 2010.
This research study was supported by a grant from the National Institute of Nursing Research and the Office of Cancer Survivorship at the National Cancer Institute (5R01-NR005332-04), USA.
Corresponding author: Andres Azuero, PhD, MBA, NB 1019F, 1530 3rd Ave. S., Birmingham, AL 35294-1210 (e-mail: firstname.lastname@example.org).