OptSig
Optimal Level of Significance for Regression and Other Statistical Tests
The optimal level of significance is calculated based on a decision-theoretic approach. The optimal level is chosen so that the expected loss from hypothesis testing is minimized. A range of statistical tests are covered, including the test for the population mean, population proportion, and a linear restriction in a multiple regression model. The details are covered in Kim and Choi (2020) doi:10.1111/abac.12172, and Kim (2021) doi:10.1080/00031305.2020.1750484.
- Version2.2
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release07/03/2022
Team
Jae H. Kim
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- Imports1 package