Opt.sig.chisq.test

degree of freedom (depends on the chosen test)

prior probability for H0, default is p = 0.5

relative loss from Type I and II errors, k = L2/L1, default is k = 1

Computes the optimal significance level for chi-squared tests

 htest

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>.

Opt.sig.chisq.test: Optimal significance level calculation for chi-squared tests

Description

Usage

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Details

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Examples