multcomp: Simultaneous Inference for General Linear Hypotheses. R package. Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book ”Multiple Comparisons Using R” (Bretz, Hothorn, Westfall, 2010, CRC Press).

References in zbMATH (referenced in 37 articles )

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  1. Lineu Alberto Cavazani de Freitas, Wagner Hugo Bonat: Hypothesis tests for multiple responses regression models in R: The htmcglm Package (2022) arXiv
  2. Bonat, Wagner H.; Petterle, Ricardo R.; Balbinot, Priscilla; Mansur, Alexandre; Graf, Ruth: Modelling multiple outcomes in repeated measures studies: comparing aesthetic eyelid surgery techniques (2021)
  3. Li, Huajiang; Zhou, Hong: A new approach to address multiplicity in hypothesis testing with constraints (2021)
  4. Markus Burkhardt, Johannes Titz: cofad: An R package and shiny app for contrast analysis (2021) not zbMATH
  5. Miljkovic, Tatjana; Grün, Bettina: Using model averaging to determine suitable risk measure estimates (2021)
  6. Wolf, Jared; Zhou, Hong: A simple data-driven fallback procedure for multiple comparisons (2021)
  7. Frank M. T. A. Busing: Monotone Regression: A Simple and Fast O(n) PAVA Implementation (2020) not zbMATH
  8. Ludwig A. Hothorn: Claiming trend in toxicological and pharmacological dose-response studies: an overview on statistical methods and related R-Software (2020) arXiv
  9. Ludwig A. Hothorn, Frank Schaarschmidt: A Tukey type trend test for repeated carcinogenicity bioassays, motivated by multiple glyphosate studies (2020) arXiv
  10. Torsten Hothorn: Most Likely Transformations: The mlt Package (2020) not zbMATH
  11. Ahmad, M. Rauf: Multiple comparisons of mean vectors with large dimension under general conditions (2019)
  12. Bogomolov, Marina; Davidov, Ori: Order restricted univariate and multivariate inference with adjustment for covariates in partially linear models (2019)
  13. Chatterjee, Debajit; Bandyopadhyay, Uttam: Testing in nonparametric ANCOVA model based on ridit reliability functional (2019)
  14. Corain, Livio; Arboretti, Rosa; Ceccato, Riccardo; Ronchi, Fabrizio; Salmaso, Luigi: Testing and ranking on round-Robin design for data sport analytics with application to basketball (2019)
  15. Hay-Jahans, Christopher: R companion to elementary applied statistics (2019)
  16. Bornkamp, Björn: Calculating quantiles of noisy distribution functions using local linear regressions (2018)
  17. Hirschauer, Norbert; Grüner, Sven; Mußhoff, Oliver; Becker, Claudia: Pitfalls of significance testing and (p)-value variability: an econometrics perspective (2018)
  18. Holmes, Susan: Statistical proof? The problem of irreproducibility (2018)
  19. Schaarschmidt, Frank: Multiple treatment comparisons in analysis of covariance with interaction, SCI for treatment covariate interaction (2017)
  20. Colombi, Roberto; Forcina, A.: Testing order restrictions in contingency tables (2016)

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