R Packages
I develop R packages and research software to support reproducible quantitative and psychometric research. My software work translates methodological research into practical tools that researchers and students can use in real-world analyses.
The packages below address problems in test scoring, missing data, differential item functioning, and diagnostic classification. Together, they reflect my broader interest in connecting methodological development with accessible and reproducible research practice.
Featured Packages
subscore
Subscore computing functions in classical test theory
subscore provides functions for computing subscores and related quantities in classical test theory.
Current version: 3.3
TestDataImputation
Missing item response imputation for test and assessment data
TestDataImputation provides methods for imputing missing item responses in test and assessment data.
Current version: 2.3
DIFplus
Multilevel Mantel–Haenszel statistics for differential item functioning detection
DIFplus provides functions for detecting differential item functioning using multilevel Mantel–Haenszel statistics.
Current version: 1.1
ROCpsych
Compute and compare diagnostic test statistics across groups
ROCpsych provides functions for computing and comparing diagnostic test statistics across groups.
Current version: 1.4
Software and Reproducible Research
My software development is closely connected to my methodological research. Rather than treating software as separate from research, I use R packages to translate methodological ideas into practical tools that researchers can implement, evaluate, and reproduce.
The packages span several complementary areas:
| Area | Package |
|---|---|
| Subscore computation | subscore |
| Missing data | TestDataImputation |
| Differential item functioning | DIFplus |
| Diagnostic accuracy | ROCpsych |
Together, these packages reflect a broader goal of developing accessible, reproducible, and methodologically grounded tools for quantitative research.