multicate v1.0.0

🎉 multicate v1.0.0 Released! 🎉

We’re excited to announce the first official release of {multicate} (v1.0.0)! 🚀
The package provides functions for performing machine learning methods that estimate theconditional average treatment effect (CATE) by combining data from multiple studies. Additionalfunctions can be used to estimate prediction intervals for the CATE in a target sample based on the aforementioned models.

✨ What's New in v1.0.0?

This initial release includes:

• Core Functionality
  • estimate_cate() estimates conditional average treatment effect (CATE) from multiple studies.
  • summary.cate() and plot.cate() (S3) and plot_vteffect() support custom summarization and visualizations.
  • predict.cate() (S3) generates prediction intervals for covariate profiles in target dataset based on CATE model.
• Built-in Dataset: dummy_tbl for easy testing and examples.
• Comprehensive Documentation: Includes examples and function help files.

🔧 Installation

You can install {multicate} using:

pak::pak("dobengjhu/multicate")

📢 Try It Out!

Check out the README and examples to get started. Your feedback is welcome—feel free to open issues or contribute!

🚀 View repo on GitHub 🚀

Happy coding! 🎯