Describe Data

Produce summaries of various types of variables. Descriptive statistics and plots are chosen automatically depending on the class of x. The intention is to provide a fast but rich summary with minimal typing.

Compute descriptive statistics for a dichotomous variable. The plot method displays absolute and relative frequencies in horizontal bar plots.

Usage

desc(x, ...)

# S3 method for class 'list'
desc(x, ...)

# S3 method for class 'Desc.list'
print(x, ...)

# S3 method for class 'data.frame'
desc(x, ...)

# S3 method for class 'Desc'
print(x, ...)

# S3 method for class 'Desc'
plot(x, ...)

# S3 method for class 'Desc.factor'
plot(x, ...)

# S3 method for class 'logical'
desc(
  x,
  ord = "level",
  conf.level = 0.95,
  include_x = TRUE,
  main = NULL,
  verbose = NULL,
  plotit = NULL,
  digits = NULL,
  ...
)

# S3 method for class 'Desc.logical'
print(x, digits = NULL, ...)

# S3 method for class 'Desc.logical'
plot(x, ...)

# S3 method for class 'Desc.numeric'
print(x, digits = NULL, ...)

# S3 method for class 'Desc.numeric'
plot(x, main = x$meta$main, ...)

# S3 method for class 'Desc.AllNA'
print(x, ...)

# S3 method for class 'Desc.AllNA'
plot(x, ...)

# S3 method for class 'formula'
desc(
  formula,
  data,
  subset,
  na.action = na.pass,
  main = NULL,
  verbose = NULL,
  plotit = NULL,
  ...
)

Arguments

x: a dichotomous numeric, integer, factor, character, or logical vector
...: further arguments passed to methods
ord: order of the levels
conf.level: confidence level of the interval (default 0.95). If set to NA, no confidence interval is calculated.
include_x: logical; if TRUE, the original vector is retained in the result
main: character string, NULL, or NA, defining the main title. By default (main = NULL) the title will be composed as: (<class(es)>). If NA, no title is printed.
verbose: integer controlling verbosity of table output. One of 1 (minimal), 2 (default), 3 (extensive). Applies to tables only.
plotit: logical. Should a plot be created? The plot type depends on the classes of the variables. Default can be defined by the option plotit, if it does not exist then it's set to TRUE.
digits: number of digits used to format relative frequencies; the default can be set with setDescToolsXOption(digits = x)
formula: formula describing the design. Depending on the function, supported forms include y ~ 1, Pair(x, y) ~ 1, y ~ group, y ~ predictor, and y ~ treatment | block
data: optional matrix or data frame (or similar; see stats::model.frame()) containing the variables in the formula. If omitted, variables are taken from environment(formula)
subset: optional expression specifying a subset of observations to be used in the analysis
na.action: function specifying how missing values are handled; passed to bedrock::resolveFormula()

Value

an object of class "Desc" with a subclass determined by the input, such as "Desc.numeric" or "Desc.qn"

an object of class c("Desc.logical", "Desc") with components:

afrq

absolute frequencies

rfrq

matrix of binomial estimates with columns:

est: point estimate of the binomial proportion
lci: lower confidence interval bound
uci: upper confidence interval bound

Details

desc() is an S3 generic that computes basic descriptive statistics depending on the class of its input. The result is an object of class "desc" with a more specific subclass such as "desc.numeric", "desc.factor" or "desc.data.frame".

For numeric vectors, summary statistics such as mean and standard deviation are computed. For factors, frequency tables are returned. For data frames, desc() is applied column-wise.

desc is a generic function. It dispatches to the method of the class of its first argument.

Typing ?desc + TAB at the prompt lists all available methods. You usually call desc(x), but direct calls like desc.numeric(x) are also possible.

Univariate descriptions

Numeric variables: desc.numeric()
Factors and character vectors: desc.factor()
Boolean variables: desc.logical()
Contingency tables: desc.table()
Dates: desc.Date()
Time series: desc.ts()

Bivariate descriptions

numeric ~ numeric: desc.nn()
numeric ~ qualitative: desc.nq()
qualitative ~ numeric: desc.qn()
qualitative ~ qualitative: desc.qq() (wrapper around desc.table())

Design The desc system separates:

computation (internal .desc_* functions)
printing (print.Desc.*)
visualization (plot.Desc.*)

Description of a dichotomous variable. This can either be a logical vector, a factor with two levels or a numeric variable with only two unique values. The confidence levels for the relative frequencies are calculated by lumen::binomCI(), method "Wilson" on a confidence level defined by conf.level.

Dichotomous variables can be condensed into a compact graphical representation. The method calculates frequencies and binomial confidence intervals and can display them as a dot plot with error bars.

Usage

Arguments

Value

Details

See also