An Application of Longitudinal Analysis with Skewed Outcomes
Azuero, A., Pisu, M., McNees, P., Burkhardt, J., Benz, R., & Meneses, K.
School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
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.
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 reviewed for longitudinal analysis using linear and generalized linear mixed models and discussed methods are applied to analyze monthly health-related out-of-pocket expenses.
While standard statistical software is available to conduct longitudinal analyses, training is necessary to understand and 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.