Nothing
## ----message=FALSE, warning=FALSE, include=FALSE------------------------------
library(knitr)
knitr::opts_chunk$set(
comment = ">",
warning = FALSE,
message = FALSE
)
options(digits = 2)
options(knitr.kable.NA = "")
set.seed(333)
## -----------------------------------------------------------------------------
library(effectsize)
## -----------------------------------------------------------------------------
min_aov <- data.frame(
Parameter = c("(Intercept)", "A", "B", "Residuals"),
Sum_Squares = c(30, 40, 10, 100),
df = c(1, 1, 2, 50)
)
## -----------------------------------------------------------------------------
.es_aov_simple(
min_aov,
type = "eta", partial = TRUE, generalized = FALSE,
include_intercept = FALSE,
ci = 0.95, alternative = "greater",
verbose = TRUE
)
## -----------------------------------------------------------------------------
min_aovlist <- data.frame(
Group = c("S", "S", "S:A", "S:A"),
Parameter = c("(Intercept)", "Residuals", "A", "Residuals"),
Sum_Squares = c(34, 21, 34, 400),
df = c(1, 12, 4, 30)
)
## -----------------------------------------------------------------------------
.es_aov_strata(
min_aovlist,
DV_names = c("S", "A"),
type = "omega", partial = TRUE, generalized = FALSE,
ci = 0.95, alternative = "greater",
verbose = TRUE,
include_intercept = TRUE
)
## -----------------------------------------------------------------------------
min_anova <- data.frame(
Parameter = c("(Intercept)", "A", "B"),
F = c(4, 7, 0.7),
df = c(1, 1, 2),
df_error = 34
)
## -----------------------------------------------------------------------------
.es_aov_table(
min_anova,
type = "eta", partial = TRUE, generalized = FALSE,
include_intercept = FALSE,
ci = 0.95, alternative = "greater",
verbose = TRUE
)
## -----------------------------------------------------------------------------
mod <- lm(mpg ~ factor(cyl) + am, mtcars)
class(mod) <- "superMODEL"
## -----------------------------------------------------------------------------
.anova_es.superMODEL <- function(model, ...) {
# Get ANOVA table
anov <- suppressWarnings(stats:::anova.lm(model))
anov <- as.data.frame(anov)
# Clean up
anov[["Parameter"]] <- rownames(anov)
colnames(anov)[2:1] <- c("Sum_Squares", "df")
# Pass
out <- .es_aov_simple(anov, ...)
# Set attribute
attr(out, "anova_type") <- 1
out
}
## ----echo=FALSE---------------------------------------------------------------
# This is for: https://github.com/easystats/easystats/issues/348
.anova_es.superMODEL <<- .anova_es.superMODEL
## -----------------------------------------------------------------------------
eta_squared(mod)
eta_squared(mod, partial = FALSE)
omega_squared(mod)
# Etc...
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