OR {GJRM} | R Documentation |
Causal odds ratio of a binary/continuous/discrete endogenous variable
Description
OR
can be used to calculate the causal odds ratio of a binary/continuous/discrete endogenous predictor/treatment, with
corresponding interval obtained using posterior simulation.
Usage
OR(x, nm.end, E = TRUE, treat = TRUE, type = "joint", ind = NULL,
n.sim = 100, prob.lev = 0.05, length.out = NULL, hd.plot = FALSE,
or.plot = FALSE,
main = "Histogram and Kernel Density of Simulated Odds Ratios",
xlab = "Simulated Odds Ratios", ...)
Arguments
x |
A fitted |
nm.end |
Name of the endogenous variable. |
E |
If |
treat |
If |
type |
This argument can take three values: |
ind |
Binary logical variable. It can be used to calculate the OR for a subset of the data. Note that it does not make sense to use |
n.sim |
Number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used
when |
prob.lev |
Overall probability of the left and right tails of the OR distribution used for interval calculations. |
length.out |
Ddesired length of the sequence to be used when calculating the effect that a continuous/discrete treatment has on a binary outcome. |
hd.plot |
If |
or.plot |
For the case of continuous/discrete endogenous variable and binary outcome, if |
main |
Title for the plot. |
xlab |
Title for the x axis. |
... |
Other graphics parameters to pass on to plotting commands. These are used only when |
Details
OR calculates the causal odds ratio for a binary/continuous/discrete treatment. Posterior simulation is used to obtain a confidence/credible interval.
Value
prob.lev |
Probability level used. |
sim.OR |
It returns a vector containing simulated values of the average OR. This is used to calculate intervals. |
Ratios |
For the case of continuous/discrete endogenous treatment and binary outcome, it returns a matrix made up of three columns containing the odds ratios for each incremental value in the endogenous variable and respective intervals. |
Author(s)
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk