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Compare MIXED and GLMMIX to Analyze Breast Cancer Longitudinal Study

The importance of choosing the type of statistical program that we use to analyze data in a longitudinal study are growing as a specialty due to the fact that computerized data analyses have become the standard for scientific research. There are many procedures in SAS ® that can be used to analyze longitudinal data. The purpose of this paper is to compare MIXED and GLIMMIX procedure in SAS to analyze data from a e longitudinal study. A randomized trial design was used in which 185 participants were assigned to a therapeutic group by teleconference (n=92) in which participants interacted in real time with each other or the control group (n=93) who received usual psychosocial care (any support used by the patient in the course of cancer treatment). The randomization was stratified by treatment type. Data were collected at baseline, the end of the intervention, and 16 weeks from baseline. A mixed-effects repeated measures model was used to assess outcome variable of social well being (social connection) by group over time. The effect of group, time and interaction effect of group by time were examined after controlling for several confounding factors. SAS is the most powerful statistical program for data analyses in a r longitudinal study.