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afex  

Analysis of Factorial Experiments
View on CRAN: Click here


Download and install afex package within the R console
Install from CRAN:
install.packages("afex")

Install from Github:
library("remotes")
install_github("cran/afex")

Install by package version:
library("remotes")
install_version("afex", "1.4-1")



Attach the package and use:
library("afex")
Maintained by
Henrik Singmann
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-08-09
Latest Update: 2023-04-17
Description:
Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex_plot() provides a high-level interface for interaction or one-way plots using ggplot2, combining raw data and model estimates. afex uses type 3 sums of squares as default (imitating commercial statistical software).
How to cite:
Henrik Singmann (2012). afex: Analysis of Factorial Experiments. R package version 1.4-1, https://cran.r-project.org/web/packages/afex. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.2-26 (2012-08-09 19:10), 0.3-42 (2012-09-17 16:02), 0.4-57 (2013-02-11 14:22), 0.5-71 (2013-05-29 17:33), 0.6-82 (2013-09-26 16:05), 0.7-90 (2013-12-04 14:56), 0.8-94 (2014-02-23 12:09), 0.9-109 (2014-04-24 10:10), 0.10-113 (2014-08-05 00:25), 0.11-131 (2014-10-12 01:56), 0.12-135 (2014-11-03 15:05), 0.13-145 (2015-01-12 22:52), 0.14-2 (2015-08-17 23:11), 0.15-2 (2015-10-25 00:22), 0.16-1 (2016-04-04 01:11), 0.17-8 (2017-04-13 23:51), 0.18-0 (2017-05-26 00:17), 0.19-1 (2018-01-08 15:06), 0.20-2 (2018-04-04 14:40), 0.21-2 (2018-06-24 19:25), 0.22-1 (2018-09-24 06:20), 0.23-0 (2019-02-19 06:30), 0.24-1 (2019-07-03 14:10), 0.25-1 (2019-08-27 20:10), 0.26-0 (2020-01-16 06:40), 0.27-2 (2020-03-28 09:20), 0.28-0 (2020-09-20 18:40), 0.28-1 (2021-01-12 16:50), 1.0-0 (2021-07-21 08:50), 1.0-1 (2021-07-22 06:40), 1.1-0 (2022-03-27 17:00), 1.1-1 (2022-04-30 01:30), 1.2-0 (2022-10-31 00:30), 1.2-1 (2023-01-09 09:40), 1.3-0 (2023-04-18 00:00), 1.3-1 (2024-02-25 15:40)
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