GFD

R package GFD: Tests for General Factorial Designs. Implemented are the Wald-type statistic, a permuted version thereof as well as the ANOVA-type statistic for general factorial designs, even with non-normal error terms and/or heteroscedastic variances, for crossed designs with an arbitrary number of factors and nested designs with up to three factors.

Keywords for this software

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References in zbMATH (referenced in 7 articles , 1 standard article )

Showing results 1 to 7 of 7.
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  1. Ditzhaus, Marc; Fried, Roland; Pauly, Markus: QANOVA: quantile-based permutation methods for general factorial designs (2021)
  2. Harrar, Solomon W.; Ronchi, Fabrizio; Salmaso, Luigi: A comparison of recent nonparametric methods for testing effects in two-by-two factorial designs (2019)
  3. Sarah Friedrich, Frank Konietschke, Markus Pauly: Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM (2018) arXiv
  4. Wang, Chunlin; Marriott, Paul; Li, Pengfei: Semiparametric inference on the means of multiple nonnegative distributions with excess zero observations (2018)
  5. Friedrich, Sarah; Brunner, Edgar; Pauly, Markus: Permuting longitudinal data in spite of the dependencies (2017)
  6. Sarah Friedrich, Frank Konietschke, Markus Pauly: GFD: An R Package for the Analysis of General Factorial Designs (2017) not zbMATH
  7. Wang, Chunlin; Marriott, Paul; Li, Pengfei: Testing homogeneity for multiple nonnegative distributions with excess zero observations (2017)