Optimal Level of Significance for Regression and Other Statistical Tests
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, Choosing the Level of Significance: A Decision-Theoretic Approach (December 18, 2017), available at SSRN: <https://ssrn.com/abstract=2652773> or <doi:10.2139/ssrn.2652773>.
See also Kim and Ji (2015) <doi:10.1016/j.jempfin.2015.08.006>.
Functions in OptSig
|Opt.sig.chisq.test||Optimal significance level calculation for chi-squared tests|
|Opt.sig.norm.test||Optimal significance level calculation for the mean of a normal distribution (known variance)|
|Opt.Sig.Chisq||Optimal Significance Level for a Chi-square test|
|Opt.Sig||Optimal Significance Level for an F-test|
|Opt.SigWeight||Weighted Optimal Significance Level for the F-test based on the assumption of normality in the error term|
|Opt.sig.2p.test||Optimal significance level calculation for the test for two proportions (same sample sizes)|
|Opt.sig.2p2n.test||Optimal significance level calculation for the test for two proportions (different sample sizes)|
|Opt.sig.anova.test||Optimal significance level calculation for balanced one-way analysis of variance tests|
|Opt.SigBoot||Optimal Significance Level for the F-test using the bootstrap|
|Opt.SigBootWeight||Weighted Optimal Significance Level for the F-test based on the bootstrap|
|data1||Data for the U.S. production function estimation|
|Opt.sig.t.test||Optimal significance level calculation for t-tests of means (one sample, two samples and paired samples)|
|Opt.sig.t2n.test||Optimal significance level calculation for two samples (different sizes) t-tests of means|
|Opt.sig.p.test||Optimal significance level calculation for proportion tests (one sample)|
|Opt.sig.r.test||Optimal significance level calculation for correlation test|
|Power.Chisq||Function to calculate the power of a Chi-square test|
|Power.F||Function to calculate the power of an F-test|
|R.OLS||Restricted OLS estimation and F-test|
Last month downloads
Include our badge in your README