LocalControl (version 1.1.4)

plot.LocalControlCS: Plots the local treatment difference as a function of radius for LocalControl.

Description

Creates a plot where the y axis represents the local treatment difference, while the x axis represents the percentage of the maximum radius. If the confidence summary (nnConfidence) is provided, the 50% and 95% confidence estimates are also plotted.

Usage

# S3 method for LocalControlCS
plot(
  x,
  ...,
  nnConfidence,
  ylim,
  legendLocation = "bottomleft",
  ylab = "LTD",
  xlab = "Fraction of maximum radius",
  main = ""
)

Arguments

x

Return object from LocalControl with "default" outcomeType.

...

Arguments passed on to graphics::plot.default

type

1-character string giving the type of plot desired. The following values are possible, for details, see plot: "p" for points, "l" for lines, "b" for both points and lines, "c" for empty points joined by lines, "o" for overplotted points and lines, "s" and "S" for stair steps and "h" for histogram-like vertical lines. Finally, "n" does not produce any points or lines.

xlim

the x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a ‘reversed axis’.

The default value, NULL, indicates that the range of the finite values to be plotted should be used.

log

a character string which contains "x" if the x axis is to be logarithmic, "y" if the y axis is to be logarithmic and "xy" or "yx" if both axes are to be logarithmic.

sub

a subtitle for the plot.

ann

a logical value indicating whether the default annotation (title and x and y axis labels) should appear on the plot.

axes

a logical value indicating whether both axes should be drawn on the plot. Use graphical parameter "xaxt" or "yaxt" to suppress just one of the axes.

frame.plot

a logical indicating whether a box should be drawn around the plot.

panel.first

an ‘expression’ to be evaluated after the plot axes are set up but before any plotting takes place. This can be useful for drawing background grids or scatterplot smooths. Note that this works by lazy evaluation: passing this argument from other plot methods may well not work since it may be evaluated too early.

panel.last

an expression to be evaluated after plotting has taken place but before the axes, title and box are added. See the comments about panel.first.

asp

the \(y/x\) aspect ratio, see plot.window.

xgap.axis,ygap.axis

the \(x/y\) axis gap factors, passed as gap.axis to the two axis() calls (when axes is true, as per default).

nnConfidence

Return object from LocalControlNearestNeighborsConfidence

ylim

The y axis bounds. Defaults to c(0,1).

legendLocation

The location to place the legend. Default "topleft".

ylab

The y axis label. Defaults to "LTD".

xlab

The x axis label. Defaults to "Fraction of maximum radius".

main

The main plot title. Default is empty.

References

• Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl: An R Package for Comparative Safety and Effectiveness Research. Journal of Statistical Software. 2020. p. 1-32. Available from: http://dx.doi.org/10.18637/jss.v096.i04

Examples

data(lindner)
# Specify clustering variables.
linVars <- c("stent", "height", "female", "diabetic",
             "acutemi", "ejecfrac", "ves1proc")

# Call Local Control once.
linRes <- LocalControl(data = lindner,
                       clusterVars = linVars,
                       treatmentColName = "abcix",
                       outcomeColName = "cardbill",
                       treatmentCode = 1)

# Plot the local treatment differences from Local Control without
# confidence intervals.
plot(linRes, ylim =  c(-6000, 3600))

#If the confidence intervals are calculated:
#linConfidence = LocalControlNearestNeighborsConfidence(
#                                      data = lindner,
#                                      clusterVars = linVars,
#                                      treatmentColName = "abcix",
#                                      outcomeColName = "cardbill",
#                                      treatmentCode = 1, nBootstrap = 100)

# Plot the local treatment difference with confidence intervals.
#plot(linRes, linConfidence)