balance.plot: Balance plot for the given covariate.

In TriMatch: Propensity Score Matching of Non-Binary Treatments

Description

If the covariate is numeric, boxplots will be drawn with red points for the mean and green error bars for the standard error. For non-numeric covariates a barplot will be drawn.

Usage

balance.plot(x, covar, model, nstrata = attr(attr(tmatch, "triangle.psa"),
  "nstrata"), label = "Covariate", ylab = "", xlab = NULL, se.ratio = 2,
  print = TRUE, legend.position = "top", x.axis.labels,
  x.axis.angle = -45, ...)

Arguments

x	results from trimatch.
covar	vector of the covariate to check balance of.
model	an integer between 1 and 3 indicating from which model the propensity scores will be used.
nstrata	number of strata to use.
label	label for the legend.
ylab	label of the y-axis.
xlab	label of the x-axis.
se.ratio	a multiplier for how large standard error bars will be.
print	print the output if the Freidman Rank Sum Test and repeated measures ANOVA (for continuous variables).
legend.position	the position of the legend. See theme.
x.axis.labels	labels for the x-axis.
x.axis.angle	angle for x-axis labels.
...	parameters passed to plot.balance.plots.

Details

A Friedman rank sum test will be performed for all covariate types, printed, and stored as an attribute to the returned object named friedman. If a continuous covariate a repeated measures ANOVA will also be performed, printed, and returned as an attribute named rmanova.

Value

a ggplot2 figure or a list of ggplot2 figures if covar is a data frame.

TriMatch documentation built on May 2, 2019, 12:37 p.m.