Nothing
## ---- echo = FALSE, message = FALSE, results = 'hide', warning = FALSE--------
cat("this will be hidden; use for general initializations.\n")
library(ANOFA)
library(ggplot2)
library(superb)
# generate some random data with no meaning
set.seed(43)
#probs #alone #ingroup #harass #shout
pr <- c(0.4/12,1.4/12,0.5/12, 2.3/12,1.0/12,0.5/12, 0.5/12,2.0/12,0.4/12, 0.5/12,2.0/12,0.5/12)
dta <- GRF( list(Gender = c("boy", "girl", "other"),
TypeOfInterplay = c("alone", "ingroup", "harrass", "shout")
),
300,
pr
)
## ---- message = FALSE, warning = FALSE----------------------------------------
dta
## ---- warning = FALSE---------------------------------------------------------
library(ANOFA)
w <- anofa(Freq ~ Gender * TypeOfInterplay, data = dta)
## ---- message=FALSE, warning=FALSE, fig.width=4, fig.height=3, fig.cap="**Figure 1**. The frequencies of the ficticious data as a function of Gender and Type of Interplay. Error bars show difference-adjusted 95% confidence intervals."----
anofaPlot(w)
## -----------------------------------------------------------------------------
summary(w)
## -----------------------------------------------------------------------------
e <- emFrequencies(w, Freq ~ TypeOfInterplay | Gender)
summary(e)
## -----------------------------------------------------------------------------
f <- contrastFrequencies(e, list(
"alone vs. harass " = c(-1, 0, +1, 0 ),
"(alone & harass) vs. shout " = c(-1/2, 0, -1/2, +1 ),
"(alone & harass & shout) vs. in-group" = c(-1/3, +1, -1/3, -1/3)
))
summary(f)
## ---- results="hold"----------------------------------------------------------
sum(summary(f)[,1]) # Gs
sum(summary(f)[,2]) # degrees of freedom
## ---- results="hold"----------------------------------------------------------
sum(summary(e)[,1]) # Gs
sum(summary(e)[,2]) # degrees of freedom
## ---- results="hold"----------------------------------------------------------
sum(summary(w)[c(3,4),1]) # Gs
sum(summary(w)[c(3,4),2]) # degrees of freedom
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