top banner top banner
index
RegularArticles
ReplicationStudies
SpecialIssues
Vignettes
EditorialBoard
Instructions4Authors
JournalGuidelines
Messages
Submission
Search publications
Analysis of Treatment-Control Pre-Post-Follow-up Design Data

Full text PDF
Bibliographic information: BibTEX format RIS format XML format APA style
Cited references information: BibTEX format APA style
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.

Pages © TQMP;
Website last modified: 2025-07-14.
Template last modified: 2022-03-04 18h27.
Page consulted on .
Be informed of the upcoming issues with RSS feed: RSS icon RSS