An application of longitudinal analysis with skewed outcomes.
BACKGROUND
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.


OBJECTIVE
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.


METHODS
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.


CONCLUSIONS
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.
Azuero
Andres
A
School of Nursing, University of Alabama at Birmingham, Birmingham, NE, USA. andreo@uab.edu
Pisu
Maria
M
McNees
Patrick
P
Burkhardt
Jeffrey
J
Benz
Rachel
R
Meneses
Karen
K
D000704:Analysis of Variance; D015982:Bias; D001943:Breast Neoplasms / Q000191:economics; D003627:Data Interpretation, Statistical; D015987:Effect Modifier, Epidemiologic; D005382:Financing, Personal / Q000191:economics; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008137:Longitudinal Studies; D015399:Nursing Research / Q000379:methods*; D016032:Randomized Controlled Trials as Topic; D012107:Research Design; D017741:Survivors