Software & Resources
This page compiles software tools and resources I have developed or contributed to throughout my career. Many of these tools were created during earlier stages of my academic work and remain available for researchers and students who may find them useful. All materials are free to use, share, or modify with appropriate acknowledgement.
Permission to Use Resources
All software and files on this website are free to use. Please note that several packages and tools listed here are not actively maintained. If you encounter bugs or issues, please report them to the current maintainers or relevant repository managers.
simsem Package
Purpose: Simulation and analysis within the structural equation modeling (SEM) framework.
Description:
- power analysis
- model fit evaluation
- planned missing data design
- simulation-based methodological research
simsem helps analysts generate data from population models or hypotheses and evaluate model performance under various conditions. It has been widely used in teaching and research involving SEM simulation studies.
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semTools Package (Contributor)
Purpose: A collection of useful SEM-related functions extending the lavaan package.
Description:
- missing data handling
- latent variable interaction modeling
- measurement invariance
- reliability estimation
- various model evaluation utilities
semTools is widely recognized for its comprehensive collection of SEM functions that remain actively used today. The package is continually expanded, and users are welcome to submit useful functions for inclusion.
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PAWS: Power Analysis and Width of Confidence Interval for Sample Size Estimation
Purpose: A planning tool for researchers conducting cluster randomized trials.
Description:
- optimal number of clusters
- optimal cluster sizes
- statistical power
- precision of effect size estimation
- cost efficiency
PAWS helps identify sample-size configurations that achieve the desired goals with the lowest cost or the narrowest confidence intervals for effect sizes.
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Contribution to the MBESS Package
MBESS is a well-known R package that provides functions for effect sizes, confidence intervals, and sample size procedures. My contributions include:
- rewriting functions for confidence intervals of reliability (e.g., alpha and omega)
- developing functions for sample size estimation to obtain desired accuracy in treatment effects, especially in cluster randomized designs
Calculators
Confidence Interval for Pearson’s correlation. Excel
Scaled Chi-square Difference Test. Excel