OptSig (2.0)

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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, 2019, Choosing the Level of Significance: A Decision-Theoretic Approach, Abacus. See also Kim and Ji (2015) .

Maintainer: Jae H. Kim
Author(s): Jae H. Kim <J.Kim@latrobe.edu.au>

License: GPL-2

Uses: pwr

Released 2 months ago.

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