p.value: Posterior Predictive Test statistics

In sergioventurini/mederrRank: Bayesian Methods for Identifying the Most Harmful Medication Errors

Posterior Predictive Test statistics

Description

This function computes posterior predictive test statistics as described in Myers et al. (2011).

Usage

p.value(reps)

Arguments

reps	list of replications created with the post.rep function.

Details

For further details see Myers et al. (2011).

Value

p-value creates a list of p-values.

Author(s)

Sergio Venturini [e-mail],

Jessica A. Myers [e-mail]

References

Myers, J. A., Venturini, S., Dominici, F. and Morlock, L. (2011), "Random Effects Models for Identifying the Most Harmful Medication Errors in a Large, Voluntary Reporting Database". Technical Report.

See Also

bhm.constr.resamp, bhm.mcmc, bhm.resample, post.rep.

Examples

## Not run: 
data("simdata", package = "mederrRank")
summary(simdata)

fit <- bhm.mcmc(simdata, nsim = 1000, burnin = 500, scale.factor = 1.1)
resamp <- bhm.resample(fit, simdata, p.resample = .1,
	k = c(3, 6, 10, 30, 60, Inf), eta = c(.5, .8, 1, 1.25, 2))
fit2 <- bhm.constr.resamp(fit, resamp, k = 3, eta = .8)
reps <- post.rep(fit2, simdata)
pvalues <- p.value(reps)

## End(Not run)

sergioventurini/mederrRank documentation built on Oct. 19, 2023, 12:40 a.m.