Description Usage Arguments Details Author(s) See Also Examples
Given predefined strata and two level treatment for a continuous covariate from a propensity score analysis,
box.psa
draws pairs of side by side boxplots corresponding to control and treatment for each stratum.
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continuous 
Vector or N X 3 dataframe or matrix. If a vector, then represents the quantitative
covariate that is being balanced within strata in a PSA. If 
treatment 
Binary vector of same length as 
strata 
A vector or factor of same length as 
boxwex 
Numeric; controls width of boxes. Default = 0.17 
offset 
Numeric; controls distance between the two boxes in each stratum. Default = 0.17 
col 
Default = 
xlab 
Label for the xaxis; default = 
legend.xy 
Binary vector giving coordinates of the legend. By default the legend is placed to the top left. 
legend.labels 
Vector of labels for the legend; default is essentially

pts 
Logical; if 
balance 
Logical; if 
trim 
If 
B 
Passed to 
... 
Other graphical parameters passed to 
Draws a pair of side by side boxplots for each stratum of a propensity score analysis. This allows visual comparisons within strata of the distribution of the given continuous covariate, and comparisons between strata as well. The number of observations in each boxplot are given below each box, and the means of paired treatment and control groups are connected.
James E. Helmreich James.Helmreich@Marist.edu
Robert M. Pruzek RMPruzek@yahoo.com
bal.ks.psa
, bal.ms.psa
, cat.psa
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 
continuous<rnorm(1000)
treatment<sample(c(0,1),1000,replace=TRUE)
strata<sample(5,1000,replace=TRUE)
box.psa(continuous, treatment, strata)
data(lindner)
attach(lindner)
lindner.ps < glm(abcix ~ stent + height + female +
diabetic + acutemi + ejecfrac + ves1proc,
data = lindner, family = binomial)
ps<lindner.ps$fitted
lindner.s5 < as.numeric(cut(ps, quantile(ps, seq(0, 1, 1/5)),
include.lowest = TRUE, labels = FALSE))
box.psa(ejecfrac, abcix, lindner.s5, xlab = "ejecfrac",
legend.xy = c(3.5,110))
lindner.s10 < as.numeric(cut(ps, quantile(ps, seq(0, 1, 1/5)),
include.lowest = TRUE, labels = FALSE))
box.psa(height, abcix, lindner.s10, xlab="height",
boxwex = .15, offset = .15, legend.xy = c(2,130), balance = TRUE)

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