box.psa {PSAgraphics} | R Documentation |
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.
box.psa(continuous, treatment = NULL, strata = NULL, boxwex = 0.17, offset = 0.17, col = c("yellow", "orange", "black", "red", "darkorange3"), xlab = "Stratum", legend.xy = NULL, legend.labels = NULL, pts = TRUE, balance = FALSE, trim = 0, B = 1000, ...)
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 continuous
has three columns, then the second and third are assumed to be the treatment and strata respectively. Missing values are not allowed. |
treatment |
Binary vector of same length as continuous representing the two treatments; can be a character vector or factor. |
strata |
A vector or factor of same length as continuous indicating the
derived strata from estimated propensity scores. May be numeric or character vector, or factor. Strata are ordered lexicographically in plot. |
boxwex |
Numeric; controls width of boxes. Default = 0.17 |
offset |
Numeric; controls distance between the two boxes in each stratum. Default = 0.17 |
col |
Color vector for the control boxes, treatment boxes, and
line connecting their means. Default = c("yellow", "orange", "black", "red", "darkorange3") . |
xlab |
Label for the x-axis; default = "Stratum" . Other standard labels may be used as well. |
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
c("Treatment (first)", "Treatment (second)", "Treatment Means Compared",
"KS p-values", "Strata-Treatment Size") where treatment names are taken from treatment .
Vector has four elements if balance = FALSE , ommitting "KS p-values". |
pts |
Logical; if TRUE then (jittered) points are added on top of the boxplots. |
balance |
Logical; if TRUE then bal.ms.psa provides a histogram of
a permutation distribution and reference statstic to assess balance across strata; bal.ks.psa
adds p-values to the graph derived from 2-sample Kologmorov-Smirnov tests of
equivalence of control/treatment distributions within each stratum. |
trim |
If balance=TRUE , defines fraction (0 to 0.5) of observations to be trimmed from each end of stratum-treatment
level before the mean is computed. See mean , bal.ms.psa . |
B |
Passed to bal.ms.psa if necessary, determines number of randomly generated
comparison statistics. Default =1000. |
... |
Other graphical parameters passed to boxplot . |
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
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)