Optimal Level of Significance for Regression and Other
Statistical Tests
R package OptSig version 2.0
Calculates the optimal level of significance 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, Jae H. and Choi, In, 2019, Choosing the Level of Significance: A Decision-Theoretic Approach, Abacus.
See also Kim and Ji (2015) <doi:10.1016/j.jempfin.2015.08.006>.
Software
Imports: pwr
Jae H. Kim <J.Kim@latrobe.edu.au>
Comprehensive R Archive Network (CRAN)
Jae H. Kim <J.Kim@latrobe.edu.au>
GPL-2
2019-09-08
application/tgz
https://CRAN.R-project.org/package=OptSig