PE can be used to calculate the sample treatment effect from a a binary bivariate model, with
corresponding interval obtained using posterior simulation.
PE(x1, idx, n.sim = 100, prob.lev = 0.05,
hd.plot = FALSE,
main = "Histogram and Kernel Density of Simulated Average Effects",
xlab = "Simulated Average Effects", ...)A fitted gjrm object.
This is useful to pick a particular individual and must be provided.
Number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used
when delta = FALSE. It may be increased if more precision is required.
Overall probability of the left and right tails of the AT distribution used for interval calculations.
If TRUE then a plot of the histogram and kernel density estimate of the simulated average effects is produced.
Title for the plot.
Title for the x axis.
Other graphics parameters to pass on to plotting commands. These are used only when hd.plot = TRUE.
Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk
PE measures the sample average effect from a binary bivariate model when a binary response (associated with a continuous outcome) takes values 0 and 1. Posterior simulation is used to obtain a confidence/credible interval.
GJRM-package, gjrm