mice: mdc – R documentation

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mdc

Graphical parameter for missing data plots

Description

mdc returns colors used to distinguish observed, missing and combined data in plotting. mice.theme return a partial list of named objects that can be used as a theme in stripplot, bwplot, densityplot and xyplot.

Usage

mdc(
  r = "observed",
  s = "symbol",
  transparent = TRUE,
  cso = grDevices::hcl(240, 100, 40, 0.7),
  csi = grDevices::hcl(0, 100, 40, 0.7),
  csc = "gray50",
  clo = grDevices::hcl(240, 100, 40, 0.8),
  cli = grDevices::hcl(0, 100, 40, 0.8),
  clc = "gray50"
)

Arguments

`r`	A numerical or character vector. The numbers 1-6 request colors as follows: 1=`cso`, 2=`csi`, 3=`csc`, 4=`clo`, 5=`cli` and 6=`clc`. Alternatively, `r` may contain the strings ' `observed`', '`missing`', or '`both`', or abbreviations thereof.
`s`	A character vector containing the strings '`symbol`' or ' `line`', or abbreviations thereof.
`transparent`	A logical indicating whether alpha-transparency is allowed. The default is `TRUE`.
`cso`	The symbol color for the observed data. The default is a transparent blue.
`csi`	The symbol color for the missing or imputed data. The default is a transparent red.
`csc`	The symbol color for the combined observed and imputed data. The default is a grey color.
`clo`	The line color for the observed data. The default is a slightly darker transparent blue.
`cli`	The line color for the missing or imputed data. The default is a slightly darker transparent red.
`clc`	The line color for the combined observed and imputed data. The default is a grey color.

Details

This function eases consistent use of colors in plots. The default follows the Abayomi convention, which uses blue for observed data, red for missing or imputed data, and black for combined data.

Value

mdc() returns a vector containing color definitions. The length of the output vector is calculate from the length of r and s. Elements of the input vectors are repeated if needed.

Author(s)

Stef van Buuren, sept 2012.

References

Sarkar, Deepayan (2008) Lattice: Multivariate Data Visualization with R, Springer.

Examples

# all six colors
mdc(1:6)

# lines color for observed and missing data
mdc(c("obs", "mis"), "lin")

mice

Multivariate Imputation by Chained Equations

v3.13.0

GPL-2 | GPL-3

Authors

Stef van Buuren [aut, cre], Karin Groothuis-Oudshoorn [aut], Gerko Vink [ctb], Rianne Schouten [ctb], Alexander Robitzsch [ctb], Patrick Rockenschaub [ctb], Lisa Doove [ctb], Shahab Jolani [ctb], Margarita Moreno-Betancur [ctb], Ian White [ctb], Philipp Gaffert [ctb], Florian Meinfelder [ctb], Bernie Gray [ctb], Vincent Arel-Bundock [ctb]

Initial release

2021-01-26

mdc