plot.SimpleTable {SimpleTable} | R Documentation |
plot.SimpleTable
summarizes a SimpleTable
object by plotting the psterior density of the prima facie and
sensitivity analysis causal effects.
plot.SimpleTable(x, estimand = c("ATE", "ATT", "ATC", "RR", "RRT", "RRC", "logRR", "logRRT", "logRRC"), percent = 95, plot.bounds = TRUE, plot.pf = TRUE, plot.sens = TRUE, plot.prior = FALSE, color.bounds = "cyan", color1.pf = "lawngreen", color2.pf = "green", color1.sens = "magenta3", color2.sens = "purple4", color.prior = "lightgray", ymax = NULL, ...)
x |
An object of class SimpleTable produced by
analyze2x2 or analyze2x2xK that is to be graphically
summarized. |
estimand |
The causal estimand of interest. Options include:
ATE (average treatment effect),
ATT (average treatment effect on the treated),
ATC (average treatment effect on the controls),
RR (relative risk),
RRT (relative risk on the treated),
RRC (relative risk on the controls),
logRR (log relative risk),
logRRT (log relative risk on the treated), and
logRRC (log relative risk on the controls).
|
percent |
A number between 0 and 100 (exclusive) giving the size of the highest posterior density regions to be calculated and plotted. Default value is 95. |
plot.bounds |
Logical value indicating whether the large-sample nonparametric bounds should be plotted. Default value is TRUE . |
plot.pf |
Logical value indicating whether the posterior
density of the prima facie causal effect should be plotted. Default
value is TRUE . |
plot.sens |
Logical value indicating whether the posterior
density of the sensitivity analysis causal effect should be plotted. Default
value is TRUE . |
plot.prior |
Logical value indicating whether the
prior density of the causal effect of interest should be plotted. Default
value is FALSE . |
color.bounds |
The color of the line segment depicting the
large-sample nonparametric bounds. Default value is cyan . |
color1.pf |
The color of the prima facie posterior density in
regions outside the percent % highest posterior density
region. Default value is lawngreen . |
color2.pf |
The color of the prima facie posterior density in
regions inside the percent % highest posterior density
region. Default value is green . |
color1.sens |
The color of the sensitivity analysis posterior
density in regions outside the percent % highest posterior
density region. Default value is magenta3 . |
color2.sens |
The color of the sensitivity analysis posterior
density in regions inside the percent % highest posterior
density region. Default value is purple4 . |
color.prior |
The color of the prior density of the causal
effect of interest. Default value is lightgray . |
ymax |
The maximum height of the y-axis. If NULL
(the default) then ymax is taken to be the maximum ordinate
of the prima facie posterior density, the sensitivity analysis
posterior density, and the prior density. |
... |
Other arguments to be passed. |
See Quinn (2008) for the a description of these plots along with the associated terminology and notation.
Kevin M. Quinn
Quinn, Kevin M. 2008. ``What Can Be Learned from a Simple Table: Bayesian Inference and Sensitivity Analysis for Causal Effects from 2 x 2 and 2 x 2 x K Tables in the Presence of Unmeasured Confounding.'' Working Paper.
ConfoundingPlot
, analyze2x2
, analyze2x2xK
, ElicitPsi
, summary.SimpleTable
## Not run: ## Example from Quinn (2008) ## (original data from Oliver and Wolfinger. 1999. ## ``Jury Aversion and Voter Registration.'' ## American Political Science Review. 93: 147-152.) ## ## Y=0 Y=1 ## X=0 19 143 ## X=1 114 473 ## ## a prior belief in an essentially negative monotonic treatment effect S.mono <- analyze2x2(C00=19, C01=143, C10=114, C11=473, a00=.25, a01=.25, a10=.25, a11=.25, b00=0.02, c00=10, b01=25, c01=3, b10=3, c10=25, b11=10, c11=0.02) ## ATE (the default) plot(S.mono) ## ATC instead of ATE plot(S.mono, estimand="ATC") ## different colors plot(S.mono, estimand="ATC", color1.pf="red", color2.pf="blue", color1.sens="gray", color2.sens="orange") ## End(Not run)