Regression model
Permutation (Randomization) Test
The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.
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Sources
- Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
- Edgington, E. S., & Onghena, P. (2007). Randomization Tests (4th ed.). CRC Press. ISBN: 978-1584885894
Related methods
Referenced by
Bayesian BootstrapBCa BootstrapBlock BootstrapBootstrap InferenceBootstrap SimulationCluster-Robust Standard ErrorsDouble BootstrapFriedman testJackknifeJackknife EstimationKruskal-Wallis testLevene and Brown-Forsythe TestMann-Whitney U testParametric BootstrapPolicy Evaluation Placebo TestRandomization InferenceRobust ANOVARobust Hausman TestRobust Mixed ModelSimulation-assisted hypothesis testing researchSn and Qn Scale EstimatorsTheil-Sen EstimatorTrimmed Mean TestTwo-Sample Kolmogorov-Smirnov TestWild BootstrapWinsorized Estimation