Power.Chisq: Function to calculate the power of a Chi-square test

In OptSig: Optimal Level of Significance for Regression and Other Statistical Tests

Function to calculate the power of a Chi-square test

Description

This function calculates the power of a Chi-square test, given the value of non-centrality parameter

Usage

Power.Chisq(df, ncp, alpha, Figure = TRUE)

Arguments

df	degree of freedom
ncp	a value of of the non-centality paramter
alpha	the level of significance
Figure	show graph if TRUE (default); No graph if FALSE

Details

See Kim and Choi (2020)

Value

Power	Power of the test
Crit.val	Critical value at alpha level of signifcance

Note

See Application Section and Appendix of Kim and Choi (2017)

Author(s)

Jae H. Kim

References

Kim and Choi, 2020, Choosing the Level of Significance: A Decision-theoretic Approach, Abacus, Wiley. <https://doi.org/10.1111/abac.12172>

See Also

Leamer, E. 1978, Specification Searches: Ad Hoc Inference with Nonexperimental Data, Wiley, New York.

Kim, JH and Ji, P. 2015, Significance Testing in Empirical Finance: A Critical Review and Assessment, Journal of Empirical Finance 34, 1-14. <DOI:http://dx.doi.org/10.1016/j.jempfin.2015.08.006>

Kim, Jae H., 2020, Decision-theoretic hypothesis testing: A primer with R package OptSig, The American Statistician. <https://doi.org/10.1080/00031305.2020.1750484.>

Examples

Power.Chisq(df=5,ncp=5,alpha=0.05,Figure=TRUE)

OptSig documentation built on July 3, 2022, 5:05 p.m.