lmerPerm: Perform Permutation Test on General Linear and Mixed Linear
Regression
We provide a solution for performing permutation tests on linear and mixed linear regression models. It
allows users to obtain accurate p-values without making distributional assumptions about the data. By
generating a null distribution of the test statistics through repeated permutations of the response variable,
permutation tests provide a powerful alternative to traditional parameter tests (Holt et al. (2023)
<doi:10.1007/s10683-023-09799-6>). In this early version, we focus on the permutation tests over observed
t values of beta coefficients, i.e.original t values generated by parameter tests. After generating a null
distribution of the test statistic through repeated permutations of the response variable, each observed t
values would be compared to the null distribution to generate a p-value. To improve the efficiency,a stop
criterion (Anscombe (1953) <doi:10.1111/j.2517-6161.1953.tb00121.x>) is adopted to force permutation to stop
if the estimated standard deviation of the value falls below a fraction of the estimated p-value. By doing so,
we avoid the need for massive calculations in exact permutation methods while still generating stable and accurate
p-values.
| Version: |
0.1.9 |
| Imports: |
lmerTest, stats |
| Published: |
2023-04-18 |
| Author: |
Wentao Zeng [aut, cre, cph] |
| Maintainer: |
Wentao Zeng <wentaozeng at aliyun.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
lmerPerm results |
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