mlpsa.difference.plot: Creates a graphic summarizing the differences between...

In multilevelPSA: Multilevel Propensity Score Analysis

Description

Creates a graphic summarizing the differences between treatment and comparison groups within and across level two clusters.

Usage

mlpsa.difference.plot(x, xlab, ylab = NULL, title = NULL,
  overall.col = "blue", overall.ci.col = "green",
  level2.point.size = NULL, level1.points = TRUE, errorbars = TRUE,
  errorbars.adjusted.ci = TRUE, level2.rug.plot = TRUE, jitter = TRUE,
  reorder = TRUE, labelLevel2 = TRUE, sd = NULL, xlim, ...)

Arguments

x	the results of mlpsa.
xlab	label for the x-axis, or NULL to exclude.
ylab	label for the y-axis, or NULL to exclude.
title	title of the figure, or NULL to exclude.
overall.col	the color of the overall results line.
overall.ci.col	the color of the overall confidence interval.
level2.point.size	the point size of level 2 points.
level1.points	logical value indicating whether level 1 strata should be plotted.
errorbars	logical value indicating whether error bars should be plotted for for each level 1.
errorbars.adjusted.ci	whether the Bonferroni adjusted error bars should be plotted (these will be dashed lines).
level2.rug.plot	logical value indicating whether a rug plot should be plotted for level 2.
jitter	logical value indicating whether level 1 points should be jittered.
reorder	logical value indicating whether the level two clusters should be reordered from largest difference to smallest.
labelLevel2	logical value indicating whether the difference for each level 2 should be labeled.
sd	If specified, effect sizes will be plotted instead of difference in the native unit.
xlim	the limits of the x-axis.
...	currently unused.

See Also

plot.mlpsa

Examples

## Not run: 
data(pisana)
data(pisa.colnames)
data(pisa.psa.cols)
mlctree = mlpsa.ctree(pisana[,c('CNT','PUBPRIV',pisa.psa.cols)], formula=PUBPRIV ~ ., level2='CNT')
student.party = getStrata(mlctree, pisana, level2='CNT')
student.party$mathscore = apply(student.party[,paste0('PV', 1:5, 'MATH')], 1, sum) / 5
results.psa.math = mlpsa(response=student.party$mathscore, 
       treatment=student.party$PUBPRIV, 
       strata=student.party$strata, 
       level2=student.party$CNT, minN=5)
mlpsa.difference.plot(results.psa.math, sd=mean(student.party$mathscore, na.rm=TRUE))

## End(Not run)

multilevelPSA documentation built on May 1, 2019, 9:19 p.m.