SurrogateRsq
Goodness-of-Fit Analysis for Categorical Data using the Surrogate R-Squared
To assess and compare the models' goodness of fit, R-squared is one of the most popular measures. For categorical data analysis, however, no universally adopted R-squared measure can resemble the ordinary least square (OLS) R-squared for linear models with continuous data. This package implement the surrogate R-squared measure for categorical data analysis, which is proposed in the study of Dungang Liu, Xiaorui Zhu, Brandon Greenwell, and Zewei Lin (2022) doi:10.1111/bmsp.12289. It can generate a point or interval measure of the surrogate R-squared. It can also provide a ranking measure of the percentage contribution of each variable to the overall surrogate R-squared. This ranking assessment allows one to check the importance of each variable in terms of their explained variance. This package can be jointly used with other existing R packages for variable selection and model diagnostics in the model-building process.
- Version0.2.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release04/24/2023
Documentation
Team
Xiaorui (Jeremy) Zhu
Brandon Greenwell
Show author detailsRolesContributorDungang Liu
Show author detailsRolesContributorZewei Lin
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 140 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 1,947 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 Sep 11, 2024 with 25 downloads.
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Dependencies
- Depends4 packages
- Suggests5 packages