| Title: | Professional Contrast Coding for OLS Models |
| Version: | 0.1.0 |
| Description: | Automates sum coding (also known as effect coding) for Ordinary Least Squares (OLS) regression models. This approach is specifically designed to handle seasonal time series and categorical variables by comparing each group to the grand mean, rather than a single baseline category. This ensures that the intercept represents the unweighted grand mean of the dependent variable. For a comprehensive overview of contrast coding systems, see the UCLA Advanced Research Computing documentation (2021) https://stats.oarc.ucla.edu/r/library/r-library-contrast-coding-systems-for-categorical-variables/. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| Imports: | stats |
| Suggests: | knitr |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2026-04-22 10:51:15 UTC; petya |
| Author: | Peti Mester [aut, cre] |
| Maintainer: | Peti Mester <petyatoth2005@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-04-23 19:40:02 UTC |
Apply PetiContrast (Sum Coding) to a Data Frame
Description
This function applies a custom sum coding (effect coding) to a specified factor column in a data frame. It is designed for OLS models where you want to compare each level to the overall trend (mean) rather than a baseline category.
Usage
apply_peticontrast(data, col_name)
Arguments
data |
A data.frame. |
col_name |
A string specifying the column name to transform. |
Value
A data.frame with the modified contrasts for the specified column.
Examples
df <- data.frame(Quarter = factor(c("Q1", "Q2", "Q3", "Q4", "Q1", "Q2")))
df_new <- apply_peticontrast(df, "Quarter")
contrasts(df_new$Quarter)