heatmap_decision: Heatmap for Decision Rules

In BACCT: Bayesian Augmented Control for Clinical Trials

Description

Visualizing a decision rule for binary endpoint using heatmap plots

Usage

heatmap_decision(object, decision.rule, y1.display = NA, y2.display = NA)

Arguments

object	An object of "BAC" class.
decision.rule	A vector of c(a,b) specifying the decision rule. See help for decision_eval function.
y1.display, y2.display	A subset of control/treatment number of events to be displayed.

Author(s)

Hongtao Zhang

Examples

## Not run: 
#borrow from 3 historical trials#
yh = c(11,300,52);nh = c(45,877,128)
#specify current trial sample sizes#
n1 = 20;n2 = 30
obj = BAC_binom(yh=yh,nh=nh,n1=n1,n2=n2,n.chain=5,
criterion.type="prob",prob.threshold=0.1,sim.mode="express")

#generate full heatmap
heatmap_decision(obj,decision.rule=c(0.05,0.15))
#generate partial heatmap
heatmap_decision(obj,decision.rule=c(0.05,0.15),y1.display=5:15,y2.display=10:25)


## End(Not run)

BACCT documentation built on May 2, 2019, 9:58 a.m.