Analysis of Treatment-Control Pre-Post-Follow-up Design Data
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 hierar...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Université d'Ottawa
2023-02-01
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| Series: | Tutorials in Quantitative Methods for Psychology |
| Subjects: | |
| Online Access: | https://www.tqmp.org/RegularArticles/vol19-1/p025/p025.pdf |
| _version_ | 1811163591824375808 |
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| author | Sharpe, Donald Cribbie, Robert A. |
| author_facet | Sharpe, Donald Cribbie, Robert A. |
| author_sort | Sharpe, Donald |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T15:07:49Z |
| format | Article |
| id | doaj.art-bad6f1f630d24d14b25aa037217362b8 |
| institution | Directory Open Access Journal |
| issn | 1913-4126 |
| language | English |
| last_indexed | 2024-04-10T15:07:49Z |
| publishDate | 2023-02-01 |
| publisher | Université d'Ottawa |
| record_format | Article |
| series | Tutorials in Quantitative Methods for Psychology |
| spelling | doaj.art-bad6f1f630d24d14b25aa037217362b82023-02-14T20:29:34ZengUniversité d'OttawaTutorials in Quantitative Methods for Psychology1913-41262023-02-01191254610.20982/tqmp.19.1.p025Analysis of Treatment-Control Pre-Post-Follow-up Design DataSharpe, DonaldCribbie, Robert A.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.https://www.tqmp.org/RegularArticles/vol19-1/p025/p025.pdfspssanovamultilevel modelshierarchical modelsmixed modelsr, spss |
| spellingShingle | Sharpe, Donald Cribbie, Robert A. Analysis of Treatment-Control Pre-Post-Follow-up Design Data Tutorials in Quantitative Methods for Psychology spss anova multilevel models hierarchical models mixed models r, spss |
| title | Analysis of Treatment-Control Pre-Post-Follow-up Design Data |
| title_full | Analysis of Treatment-Control Pre-Post-Follow-up Design Data |
| title_fullStr | Analysis of Treatment-Control Pre-Post-Follow-up Design Data |
| title_full_unstemmed | Analysis of Treatment-Control Pre-Post-Follow-up Design Data |
| title_short | Analysis of Treatment-Control Pre-Post-Follow-up Design Data |
| title_sort | analysis of treatment control pre post follow up design data |
| topic | spss anova multilevel models hierarchical models mixed models r, spss |
| url | https://www.tqmp.org/RegularArticles/vol19-1/p025/p025.pdf |
| work_keys_str_mv | AT sharpedonald analysisoftreatmentcontrolprepostfollowupdesigndata AT cribbieroberta analysisoftreatmentcontrolprepostfollowupdesigndata |