CSTE

A uniform statistical inferential tool in making individualized treatment decisions, which implements the methods of Ma et al. (2017)[https://doi.org/10.1177%2F0962280214541724] and Guo et al. (2021)[https://doi.org/10.1080%2F01621459.2020.1865167]. It uses a flexible semiparametric modeling strategy for heterogeneous treatment effect estimation in high-dimensional settings and can gave valid confidence bands. Based on it, one can find the subgroups of patients that benefit from each treatment, thereby making individualized treatment selection.

Last 30 days

This package has been downloaded 511 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,505 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Feb 20, 2025 with 65 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.