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######
######		Title: Session4Code.R
######		Author: D. Gillen
######		Date: 08.14.2013 (UW Summer Institue in Biostatistics - Group Sequential Methods)
######		Description:	Code for Session 4 (Bayesian evaluation of designs)			
######
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library(RCTdesign)
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#####
#####	Define design used in sepsis trial case study
#####
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Futility.8 <- seqDesign("prop",test="less",sample.size=c(.25,.5,.75,1)*1700,
		null=0.30,alt=0.23,power="calculate",
		nbr.analyses=4, P=c(1,0.8))


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#####	Operating characteristics
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seqEvaluate(Futility.8)	


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#####
#####	Bayesian boundaries for Futility.8
#####
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#####	Dogmatic priors
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changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.09,priorVariation=0.015^2))
changeSeqScale(Futility.8,seqScale("B",priorTheta= 0.02,priorVariation=0.015^2))
changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.04,priorVariation=0.015^2))

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#####	Changing thresholds
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Futility.8$hypotheses
changeSeqScale(Futility.8,seqScale("B", threshold=-0.06, priorTheta=-0.09,priorVariation=0.015^2))

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#####	Noninformative prior
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changeSeqScale(Futility.8,seqScale("B",priorTheta= 0.02,priorVariation=Inf))

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#####	Code to generate latex table in the notes
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tbl <- rbind(
	cbind(c(1:4,1:4),as.vector(Futility.8$bou[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.09,priorVariation=0.015^2))[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.04,priorVariation=0.015^2))[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta= 0.02,priorVariation=0.015^2))[,c(1,4)])),
	cbind(c(1:4,1:4),as.vector(Futility.8$bou[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.09,priorVariation=0.04^2))[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.04,priorVariation=0.04^2))[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta= 0.02,priorVariation=0.04^2))[,c(1,4)])),
	cbind(c(1:4,1:4),as.vector(Futility.8$bou[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.09,priorVariation=Inf))[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta=-0.04,priorVariation=Inf))[,c(1,4)]),
		as.vector(changeSeqScale(Futility.8,seqScale("B",priorTheta= 0.02,priorVariation=Inf))[,c(1,4)])))
round(rbind(cbind(tbl[1:4,],tbl[5:8,2:5]),
		cbind(tbl[9:12,],tbl[13:16,2:5]),cbind(tbl[17:20,],tbl[21:24,2:5])),3)	
		


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###### Bayesian predictive probabilities assuming -.06 a marketable effect
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1-changeSeqScale(Futility.8,seqScale("H",priorTheta=-0.04,priorVariation=.04^2,threshold=-.06))
1-changeSeqScale(Futility.8,seqScale("H",priorTheta=-0.04,priorVariation=Inf,threshold=-.06))

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#####	Compare predictive probability with conditional power
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1-changeSeqScale(Futility.8,seqScale("H",priorTheta=-0.04,priorVariation=1e-10,threshold=-.06))
1-changeSeqScale(Futility.8,seqScale("C",hypTheta=-0.04,threshold=-.06))