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Analysis of Treatment-Control Pre-Post-Follow-up Design Data

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Doi: 10.20982/tqmp.19.1.p025

Sharpe, Donald , Cribbie, Robert A.
25-46
Keywords: SPSS , ANOVA , Multilevel Models , Hierarchical Models , Mixed Models , Statistics
Tools: R, SPSS
(no sample data)   (Appendix)

The treatment-control pre-post-follow-up (TCPPF) design is a popular means to demonstrate that a treatment group is superior to a control group over time. The TCPPF design can be analyzed using traditional methods (e.~g., between-within ANOVA) or with modern multilevel (also known as mixed or hierarchical) modeling. In spite of TCPPF’s widespread popularity, there is sparse and confusing guidance for applied researchers on how to analyze data from TCPPF designs using SPSS, one of the most popular software packages for data analysis. We present an introductory tutorial on methods for analyzing TCPPF data. Advantages, disadvantages, and cautions related to applying these approaches are discussed.


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