Super Code is an interactive Jamovi module designed to simplify the generation, understanding, and application of coding schemes on categorical variables.
Super Code provides an intuitive, transposed preview of the recode variables along with clear semantic descriptions of the mathematical comparisons executed by each contrast (e.g. Level B - Level A instead of just coding numbers). It also allows you to append the computed contrast columns directly to your jamovi dataset for downstream analyses.
Since the module is written as a jamovi R package, you can compile and install it directly using jmvtools inside your R environment:
# Install jmvtools if you haven't already
install.packages('jmvtools', repos='https://jamovi.org/cran')
# Inside the project root directory, run:
jmvtools::install()If you are running jamovi/R under Nix, load the environment containing RStudio/jamovi and execute jmvtools::install() from the R console.
- Open jamovi and load your dataset.
- Select Regression > Recode Variables from the analysis menu.
- Drag your categorical/factor variables into the Variables box.
- Customize the contrast settings for each variable under the options list:
- Choose the coding scheme (e.g., Dummy, Helmert, Forward Difference).
- Select the desired reference level (if supported by the coding scheme).
- Enable/disable standardization.
- Inspect the Recode Variables Preview table to see exactly what comparisons are being set up.
- Click the Add Columns button to append the coded columns back into your jamovi spreadsheet for regression or general linear modeling.
| Coding Scheme | Parameter Row | Contrast / Comparison Task |
|---|---|---|
| Dummy (Treatment) | dummy j |
|
| Simple | simple j |
|
| Deviation (Sum) | deviation j |
|
| Orthogonal Polynomial | poly j |
Orthogonal polynomial trend of degree |
| Helmert | helmert j |
|
| Reverse Helmert | revhelmert j |
|
| Forward Difference | forward j |
|
| Backward Difference | backward j |
This project is licensed under the GPL (>= 3) License.