AT2: Average treatment effect from a two-part model
In SemiParBIVProbit: Semiparametric Copula Regression Models

Description Usage Arguments Details WARNINGS Author(s) See Also Examples

AT2 can be used to calculate the sample average treatment effect from a two-part model, with corresponding interval obtained using posterior simulation.

AT2(x1, x2, index1, index2, n.sim = 100, prob.lev = 0.05, 
    hd.plot = FALSE, 
    main = "Histogram and Kernel Density of Simulated Average Effects", 
    xlab = "Simulated Average Effects", ...)

`x1`	A fitted `SemiParBIVProbit` object as produced by `SemiParBIVProbit()`.
`x2`	A fitted `SemiParBIVProbit` object as produced by `SemiParBIVProbit()`.
`index1`	This is useful to pick a particular individual.
`index2`	As above.
`n.sim`	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.
`prob.lev`	Overall probability of the left and right tails of the AT distribution used for interval calculations.
`hd.plot`	If `TRUE` then a plot of the histogram and kernel density estimate of the simulated average effects is produced. This can only be produced when `delta = FALSE`.
`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 `hd.plot = TRUE`.

AT measures the sample average effect from a two-part 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.

This function is not suitable for SemiParBIVProbit().

Maintainer: Giampiero Marra giampiero.marra@ucl.ac.uk

SemiParBIVProbit-package, SemiParBIVProbit, summary.SemiParBIVProbit