Description Usage Arguments Details Author(s) References See Also Examples
summary.SimpleTable
summarizes a
SimpleTable
object by printing the mode, mean, standard
deviation, and percent
% highest density region of the prima
facie and sensitivity analysis posterior densities. Large-sample
nonparametric bounds for the estimand of interest are also
reported. Summaries of the prior distribution are also reported in
situations where these summaries are numerically stable.
1 2 3 4 5 |
object |
An object of class |
estimand |
The causal estimand of interest. Options include:
|
percent |
A number between 0 and 100 (exclusive) giving the size of the highest posterior density regions to be calculated and printed. Default value is 95. |
... |
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
, plot.SimpleTable
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## 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)
summary(S.mono)
## ATC instead of ATE
summary(S.mono, estimand="ATC")
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.