add.ps: add p-values from t-tests

In plotrix: Various Plotting Functions

add p-values from t-tests

Description

Adds p-values comparing the different cells at each x-axis position with a reference cell. Uses a syntax similar to ‘⁠raw.means.plot2⁠’.

Usage

 add.ps(data, col.id, col.offset, col.x, col.value, fun.aggregate = "mean",
 ref.offset = 1, prefixes,alternative = c("two.sided", "less", "greater"),
 mu = 0, paired = FALSE, var.equal = FALSE, lty = 0, ...)

Arguments

data	A ‘⁠data.frame⁠’
col.id	‘⁠character⁠’ vector specifying the id column.
col.offset	‘⁠character⁠’ vector specifying the offset column.
col.x	‘⁠character⁠’ vector specifying the x-axis column.
col.value	‘⁠character⁠’ vector specifying the data column.
fun.aggregate	Function or function name used for aggregating the results. Default is ‘⁠"mean"⁠’.
ref.offset	Scalar ‘⁠numeric⁠’ indicating the reference level to be tested against. The default is 1 corresponding to ‘⁠levels(factor(d[,col.offset]))[1]⁠’.
prefixes	‘⁠character⁠’ vector of the indices for the p-values. If missing corresponds to ‘⁠levels(factor(d.new[,col.offset]))[-ref.offset]⁠’.
alternative	same as in t.test
mu	same as in t.test
paired	same as in t.test
var.equal	same as in t.test
lty	line type of axis, Default is 0 (i.e., no line).
...	further arguments passed to axis.

Details

This function computes t-tests comparing the values at each x-axis position for each condition against the reference condition at and adds the p-values to the axis.

This functions uses the same syntax as raw.means.plot2 and should be used in addition to it. Note that values are ordered according to the ‘⁠col.id⁠’ so ‘⁠paired = TRUE⁠’ should be fine.

Value

axis is plotted.

Author(s)

Henrik Singmann

See Also

raw.means.plot as the accompanying main functions.

Examples

## Not run: 
#The examples uses the OBrienKaiser dataset from car and needs reshape.
# This extends the examples from raw.means.plot
require(reshape)
require(car)
data(OBrienKaiser)
OBKnew <- cbind(factor(1:nrow(OBrienKaiser)), OBrienKaiser)
colnames(OBKnew)[1] <- "id"
OBK.long <- melt(OBKnew)
OBK.long[, c("measurement", "time")] <-
 t(vapply(strsplit(as.character(OBK.long$variable), "\\."),  "[", c("", "")))

# For this example the position at each x-axis are within-subject comparisons!
raw.means.plot2(OBK.long, "id", "measurement", "gender", "value")
 add.ps(OBK.long, "id", "measurement", "gender", "value", paired = TRUE)
 #reference is "fup"

raw.means.plot2(OBK.long, "id", "measurement", "gender", "value")
add.ps(OBK.long, "id", "measurement", "gender", "value", ref.offset = 2,
 paired = TRUE) #reference is "post"

# Use R's standard (i.e., Welch test)
raw.means.plot2(OBK.long, "id", "treatment", "gender", "value")
add.ps(OBK.long, "id", "treatment", "gender", "value",
 prefixes = c("p(control vs. A)", "p(control vs. B)"))

# Use standard t-test
raw.means.plot2(OBK.long, "id", "treatment", "gender", "value")
add.ps(OBK.long, "id", "treatment", "gender", "value", var.equal = TRUE,
 prefixes = c("p(control vs. A)", "p(control vs. B)"))


## End(Not run)

plotrix documentation built on Nov. 10, 2023, 5:07 p.m.