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cff-version: 1.2.0
message: 'To cite package "lmerPerm" in publications use:'
type: software
license: GPL-3.0-only
title: 'lmerPerm: Perform Permutation Test on General Linear and Mixed Linear Regression'
version: 0.1.9
doi: 10.32614/CRAN.package.lmerPerm
abstract: 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) <https://doi.org/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) <https://doi.org/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.
authors:
- family-names: Zeng
  given-names: Wentao
  email: wentaozeng@aliyun.com
repository: https://awquinlan.r-universe.dev
commit: 7cb2b9e6ecd10bac78efe8962daf3a53d6922407
date-released: '2023-04-18'
contact:
- family-names: Zeng
  given-names: Wentao
  email: wentaozeng@aliyun.com