mi_trellisplot: Trellis Conditional Scatterplot for Imputed Datasets

In mmaechler/miP: Multiple Imputation Plots

Description

Draws Trellis conditional scatterplots for imputed datasets. Imputed values by default are drawn in red, observed in blue.

Usage

mi_trellisplot(x, var, input, nr = 1, eqnr = 3, ol = 0.1,
             main = NULL,
             col = c("blue","red"), pch = 16, font.main = 2, ...)

Arguments

x	vector of variablenames that should be plotted on x- and y-axis.
var	defines the variable that is splitted continuously in equal intervals or a categorical variable.
input	MI object produced by mi, mice or Amelia.
nr	number of the imputation chain that should be plotted.
eqnr	number of intervals var should be splitted into.
ol	defines the overlap rate between the intervalls.

main	main title; by default the conditioning formula.
col	vector of length two, specifying the colors for observed and imputed values, respectively.
pch, font.main	plot attributes, passed to xyplot().
...	potentially further arguments passed to xyplot().

Author(s)

Paul Brix; tweaks by Martin Maechler

See Also

xyplot from package lattice

Examples

data(FLAS)
require("mice")
FLASmi <- mice(FLAS)
mi_trellisplot(x=c("FLAS","vSAT"), var="eng", FLASmi, eqnr=5)

mmaechler/miP documentation built on May 23, 2019, 5 a.m.