descriptives: Descriptives
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descriptives

R Documentation

Descriptives

Description

Descriptives are an assortment of summarising statistics, and visualizations which allow exploring the shape and distribution of data. It is good practice to explore your data with descriptives before proceeding to more formal tests.

Usage

descriptives(data, vars, splitBy = NULL, freq = FALSE,
  desc = "columns", hist = FALSE, dens = FALSE, bar = FALSE,
  barCounts = FALSE, box = FALSE, violin = FALSE, dot = FALSE,
  dotType = "jitter", boxMean = FALSE, boxLabelOutliers = TRUE,
  qq = FALSE, n = TRUE, missing = TRUE, mean = TRUE,
  median = TRUE, mode = FALSE, sum = FALSE, sd = TRUE,
  variance = FALSE, range = FALSE, min = TRUE, max = TRUE,
  se = FALSE, ci = FALSE, ciWidth = 95, iqr = FALSE,
  skew = FALSE, kurt = FALSE, sw = FALSE, pcEqGr = FALSE,
  pcNEqGr = 4, pc = FALSE, pcValues = "25,50,75", extreme = FALSE,
  extremeN = 5, formula)

Arguments

`data`	the data as a data frame
`vars`	a vector of strings naming the variables of interest in `data`
`splitBy`	a vector of strings naming the variables used to split `vars`
`freq`	`TRUE` or `FALSE` (default), provide frequency tables (nominal, ordinal variables only)
`desc`	`'rows'` or `'columns'` (default), display the variables across the rows or across the columns (default)
`hist`	`TRUE` or `FALSE` (default), provide histograms (continuous variables only)
`dens`	`TRUE` or `FALSE` (default), provide density plots (continuous variables only)
`bar`	`TRUE` or `FALSE` (default), provide bar plots (nominal, ordinal variables only)
`barCounts`	`TRUE` or `FALSE` (default), add counts to the bar plots
`box`	`TRUE` or `FALSE` (default), provide box plots (continuous variables only)
`violin`	`TRUE` or `FALSE` (default), provide violin plots (continuous variables only)
`dot`	`TRUE` or `FALSE` (default), provide dot plots (continuous variables only)
`dotType`	.
`boxMean`	`TRUE` or `FALSE` (default), add mean to box plot
`boxLabelOutliers`	`TRUE` (default) or `FALSE`, add labels with the row number to the outliers in the box plot
`qq`	`TRUE` or `FALSE` (default), provide Q-Q plots (continuous variables only)
`n`	`TRUE` (default) or `FALSE`, provide the sample size
`missing`	`TRUE` (default) or `FALSE`, provide the number of missing values
`mean`	`TRUE` (default) or `FALSE`, provide the mean
`median`	`TRUE` (default) or `FALSE`, provide the median
`mode`	`TRUE` or `FALSE` (default), provide the mode
`sum`	`TRUE` or `FALSE` (default), provide the sum
`sd`	`TRUE` (default) or `FALSE`, provide the standard deviation
`variance`	`TRUE` or `FALSE` (default), provide the variance
`range`	`TRUE` or `FALSE` (default), provide the range
`min`	`TRUE` or `FALSE` (default), provide the minimum
`max`	`TRUE` or `FALSE` (default), provide the maximum
`se`	`TRUE` or `FALSE` (default), provide the standard error
`ci`	`TRUE` or `FALSE` (default), provide confidence intervals for the mean
`ciWidth`	a number between 50 and 99.9 (default: 95), the width of confidence intervals
`iqr`	`TRUE` or `FALSE` (default), provide the interquartile range
`skew`	`TRUE` or `FALSE` (default), provide the skewness
`kurt`	`TRUE` or `FALSE` (default), provide the kurtosis
`sw`	`TRUE` or `FALSE` (default), provide Shapiro-Wilk p-value
`pcEqGr`	`TRUE` or `FALSE` (default), provide quantiles
`pcNEqGr`	an integer (default: 4) specifying the number of equal groups
`pc`	`TRUE` or `FALSE` (default), provide percentiles
`pcValues`	a comma-sepated list (default: 25,50,75) specifying the percentiles
`extreme`	`TRUE` or `FALSE` (default), provide N most extreme (highest and lowest) values
`extremeN`	an integer (default: 5) specifying the number of extreme values
`formula`	(optional) the formula to use, see the examples

Value

A results object containing:

`results$descriptives`					a table of the descriptive statistics
`results$descriptivesT`					a table of the descriptive statistics
`results$frequencies`					an array of frequency tables
`results$extremeValues`					an array of extreme values tables
`results$plots`					an array of descriptive plots

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$descriptives$asDF

as.data.frame(results$descriptives)

Examples


data('mtcars')
dat <- mtcars

# frequency tables can be provided for factors
dat$gear <- as.factor(dat$gear)

descriptives(dat, vars = vars(mpg, cyl, disp, gear), freq = TRUE)

#
#  DESCRIPTIVES
#
#  Descriptives
#  -------------------------------------------
#               mpg     cyl     disp    gear
#  -------------------------------------------
#    N            32      32      32      32
#    Missing       0       0       0       0
#    Mean       20.1    6.19     231    3.69
#    Median     19.2    6.00     196    4.00
#    Minimum    10.4    4.00    71.1       3
#    Maximum    33.9    8.00     472       5
#  -------------------------------------------
#
#
#  FREQUENCIES
#
#  Frequencies of gear
#  --------------------
#    Levels    Counts
#  --------------------
#    3             15
#    4             12
#    5              5
#  --------------------
#

# spliting by a variable
descriptives(formula = disp + mpg ~ cyl, dat,
    median=F, min=F, max=F, n=F, missing=F)

# providing histograms
descriptives(formula = mpg ~ cyl, dat, hist=T,
    median=F, min=F, max=F, n=F, missing=F)

# splitting by multiple variables
descriptives(formula = mpg ~ cyl:gear, dat,
    median=F, min=F, max=F, missing=F)

jmv documentation built on Oct. 12, 2023, 5:13 p.m.