bhpm.ptheta: Reports the posterior probability that theta (the increase in...

In bhpm: Bayesian Hierarchical Poisson Models for Multiple Grouped Outcomes with Clustering

Description

This function reports the posterior probability that theta is positive negative or zero, i.e. that there is an increase, decrease, or no difference in the log odds of an outcome being associated with treatment.

Usage

	bhpm.ptheta(raw)

Arguments

raw	The output from a call to one of bhpm.cluster.BB.hier3, bhpm.cluster.1a.hier3, bhpm.cluster.BB.hier2, bhpm.cluster.1a.hier2.

Value

A data frame containing the columns: Trt.Grp, Cluster, Outcome.Grp, Outcome, ptheta, ptheta.pos, ptheta.zero, ptheta.neg.

Author(s)

R. Carragher

Examples

data(bhpm.cluster.data1)
data <- subset(bhpm.cluster.data1, Cluster == '0.0-180.0' | Cluster == '180.0-360.0')
raw = bhpm.npm(data, burnin = 10, iter = 100)
p = bhpm.ptheta(raw)
head(p, 2)


data(bhpm.cluster.data1)
raw = bhpm.npm(bhpm.cluster.data1)
p = bhpm.ptheta(raw)
head(p, 2)

bhpm documentation built on April 1, 2020, 5:09 p.m.