plotrix (version 3.6-4)

add.ps: 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.

Value

axis is plotted.

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.

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)