Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(SimplyAgree)
## -----------------------------------------------------------------------------
a1 = agree_test(x = reps$x,
y = reps$y,
agree.level = .8)
## -----------------------------------------------------------------------------
print(a1)
## ---- fig.width=6, fig.height=6-----------------------------------------------
plot(a1, type = 1)
plot(a1, type = 2)
## -----------------------------------------------------------------------------
a2 = agree_reps(x = "x",
y = "y",
id = "id",
data = reps,
agree.level = .8)
## -----------------------------------------------------------------------------
print(a2)
## ---- fig.width=6, fig.height=6-----------------------------------------------
plot(a2, type = 1)
plot(a2, type = 2)
## -----------------------------------------------------------------------------
a3 = agree_nest(x = "x",
y = "y",
id = "id",
data = reps,
agree.level = .8)
## -----------------------------------------------------------------------------
print(a3)
## ---- fig.width=6, fig.height=6-----------------------------------------------
plot(a3, type = 1)
plot(a3, type = 2)
## ----warning=FALSE,eval=FALSE-------------------------------------------------
# a4 = loa_mixed(data = recpre_long,
# diff = "diff",
# condition = "trial_condition",
# id = "id",
# plot.xaxis = "AM",
# replicates = 199,
# type = "perc")
## -----------------------------------------------------------------------------
sf <- matrix(
c(9, 2, 5, 8,
6, 1, 3, 2,
8, 4, 6, 8,
7, 1, 2, 6,
10, 5, 6, 9,
6, 2, 4, 7),
ncol = 4,
byrow = TRUE
)
colnames(sf) <- paste("J", 1:4, sep = "")
rownames(sf) <- paste("S", 1:6, sep = "")
#sf #example from Shrout and Fleiss (1979)
dat = as.data.frame(sf)
## -----------------------------------------------------------------------------
test1 = reli_stats(
data = dat,
wide = TRUE,
col.names = c("J1", "J2", "J3", "J4")
)
## -----------------------------------------------------------------------------
print(test1)
## ---- fig.width=6, fig.height=6-----------------------------------------------
plot(test1)
## -----------------------------------------------------------------------------
power_res <- blandPowerCurve(
samplesizes = seq(10, 100, 1),
mu = 0.5,
SD = 2.5,
delta = c(6,7),
conf.level = c(.90,.95),
agree.level = c(.8,.9)
)
head(power_res)
## -----------------------------------------------------------------------------
find_n(power_res, power = .8)
## ----fig.width=6, fig.height=6------------------------------------------------
plot(power_res)
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