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) , and Kim (2021) .


Reference manual

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install.packages("OptSig")

2.2 by Jae H. Kim, 4 years ago


Browse source code at https://github.com/cran/OptSig


Authors: Jae H. Kim <jaekim8080@gmail.com>


Documentation:   PDF Manual  


GPL-2 license


Imports pwr


See at CRAN