plot.LocalControlCS | R Documentation |
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.
## S3 method for class 'LocalControlCS' plot( x, ..., nnConfidence, ylim, legendLocation = "bottomleft", ylab = "LTD", xlab = "Fraction of maximum radius", main = "" )
x |
Return object from LocalControl with "default" outcomeType. |
... |
Arguments passed on to |
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. |
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
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)
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