Nothing
## ----echo=FALSE-------------------------------------------------------------------------
req_suggested_packages <- c("see", "performance", "ggplot2")
pcheck <- lapply(req_suggested_packages, requireNamespace,
quietly = TRUE)
if (any(!unlist(pcheck))) {
message("Required package(s) for this vignette are not available/installed and code will not be executed.")
knitr::opts_chunk$set(eval = FALSE)
}
## ----set-options, echo=FALSE, cache=FALSE-----------------------------------------------
options(width = 90)
knitr::opts_chunk$set(dpi=72)
## ----message=FALSE----------------------------------------------------------------------
library(afex)
library(performance) # for assumption checks
## ---------------------------------------------------------------------------------------
data(obk.long, package = "afex")
o1 <- aov_ez("id", "value", obk.long,
between = c("treatment", "gender"))
check_homogeneity(o1)
## ---------------------------------------------------------------------------------------
data("fhch2010", package = "afex")
a1 <- aov_ez("id", "log_rt", fhch2010,
between = "task",
within = c("density", "frequency", "length", "stimulus"))
## ---------------------------------------------------------------------------------------
check_sphericity(a1)
## ----eval = FALSE-----------------------------------------------------------------------
# afex_options(
# correction_aov = "GG", # or "HF"
# emmeans_model = "multivariate"
# )
## ---------------------------------------------------------------------------------------
data("stroop", package = "afex")
stroop1 <- subset(stroop, study == 1)
stroop1 <- na.omit(stroop1)
s1 <- aov_ez("pno", "rt", stroop1,
within = c("condition", "congruency"))
is_norm <- check_normality(s1)
plot(is_norm)
plot(is_norm, type = "qq")
## ---------------------------------------------------------------------------------------
plot(is_norm, type = "qq", detrend = TRUE)
## ---------------------------------------------------------------------------------------
s2 <- aov_ez("pno", "rt", stroop1,
transformation = "log",
within = c("condition", "congruency"))
is_norm <- check_normality(s2)
plot(is_norm, type = "qq", detrend = TRUE)
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