compmeans: Means of a numerical vector according to a factor

In descr: Descriptive Statistics

Means of a numerical vector according to a factor

Description

Calculates the means of a numerical vector according to a factor.

Usage

compmeans(x, f, w, sort = FALSE, maxlevels = 60,
          user.missing, missing.include = FALSE,
          plot = getOption("descr.plot"),
          relative.widths = TRUE, col = "lightgray",
          warn = getOption("descr.warn"), ...)

Arguments

x	A numeric vector.
f	A factor.
w	Optional vector with weights.
sort	If TRUE, sorts the lines by the means values.
maxlevels	Maximum number of levels that x converted into factor should have.
user.missing	Character vector, indicating what levels of f must be treated as missing values.
missing.include	If TRUE, then NA values, if present in f, are included as level "NA". You can change the new level label by setting the value of descr.na.replacement option. Example: options(descr.na.replacement = "Missing").
plot	Logical: if TRUE (default), a boxplot is produced. You may put options(descr.plot = FALSE) in your ‘.Rprofile’ to change the default function behavior.
relative.widths	If TRUE, the boxes widths will be proportional to the number of elements in each level of f.
col	Vector with the boxes colors.
warn	Warn if conversion from factor into numeric or from numeric into factor was performed and if missing values were dropped (default: TRUE).
...	Further arguments to be passed to either boxplot (if w is missing) or bxp (for w weighted boxplot).

Value

A matrix with class c("matrix", "meanscomp") with labels attributes for x and f. The returned object can be plotted, generating a boxplot of x grouped by f.

Author(s)

Jakson A. Aquino [e-mail], with code for weighted boxplots written by Stefan Kraft for simPopulation package.

See Also

boxplot.

Examples

sex <- factor(c(rep("F", 900), rep("M", 900)))
income <- 100 * (rnorm(1800) + 5)
weight <- rep(1, 1800)
weight[sex == "F" & income > 500] <- 3
attr(income, "label") <- "Income"
attr(sex, "label") <- "Sex"
compmeans(income, sex, col = "lightgray", ylab = "income", xlab = "sex")
comp <- compmeans(income, sex, weight, plot = FALSE)
plot(comp, col = c("pink", "lightblue"), ylab = "income", xlab = "sex")

library(xtable)
# If the decimal separator in your country is a comma:
# options(OutDec = ",")
print(xtable(comp, caption = "Income according to sex", label = "tab:incsx"))

descr documentation built on Nov. 28, 2023, 1:10 a.m.