https://github.com/karsterr/repeated-measurement
An R-based workflow for conducting repeated measures ANOVA using the ez package, with data wrangling via tidyverse and visualization through ggplot2. Includes data import, transformation to long format, statistical analysis, and graphical summary.
https://github.com/karsterr/repeated-measurement
anove data-analysis experimental-design ezanove ggplot2 r repeated-measurements rstats statistics tidyverse
Last synced: 9 months ago
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An R-based workflow for conducting repeated measures ANOVA using the ez package, with data wrangling via tidyverse and visualization through ggplot2. Includes data import, transformation to long format, statistical analysis, and graphical summary.
- Host: GitHub
- URL: https://github.com/karsterr/repeated-measurement
- Owner: karsterr
- Created: 2025-05-09T10:50:40.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-09T10:51:40.000Z (about 1 year ago)
- Last Synced: 2025-09-16T16:55:48.887Z (9 months ago)
- Topics: anove, data-analysis, experimental-design, ezanove, ggplot2, r, repeated-measurements, rstats, statistics, tidyverse
- Language: R
- Homepage:
- Size: 153 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Repeated Measures ANOVA in R with ezANOVA
## 📦 Packages Used
- tidyverse
- readxl
- ez
- knitr
- ggplot2
## 📊 Analysis Overview
The analysis assumes that each subject has multiple measurements across different time points (or conditions), making it suitable for within-subject experimental designs.
The core steps include:
1. Loading and preparing the data
2. Reshaping it to long format for ANOVA
3. Running `ezANOVA()` with Type 3 sums of squares
4. Summarizing and plotting results
## 🖼 Example Plot
The script produces a line plot showing individual subject trends and the overall mean with standard error bars across test times.
## 📁 File Structure
- `tekrarli_olcum_ornek_no_id.xlsx`: Example dataset
- `anova_script.R`: Main analysis script
- `README.md`: Project overview
## 🔍 Future Improvements
- Exporting results to formatted tables (e.g., Word/HTML)
- Adding post-hoc comparisons
- Supporting between-subjects factors
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Feel free to clone, modify, and use this workflow in your own repeated measures analysis!
**NOTE :** This is my school project.