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######
######		Title: Session2Code.q
######		Author:	D. Gillen
######		Date: 08.14.2013 (UW Summer Institue in Biostatistics - Group Sequential Methods)
######		Description:	Code for Session 2 (Fixed Sample Study Design)					
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library( RCTdesign )
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#####	Sepsis Trial
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#####	Specification of initial design
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binomFixed <- seqDesign( prob.model = "proportions", arms = 2, null.hypothesis = .3, 
			alt.hypothesis = 0.25, ratio = c(1., 1.), nbr.analyses = 1, 
			test.type = "less", power = 0.80, alpha = 0.025 )
binomFixed

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#####	Display boundaries on normalized Z-statistic scale
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seqBoundary( binomFixed, scale="Z" )

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#####	Evaluation of operating characteristics
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seqInference( binomFixed )
seqPlotPower( binomFixed )
seqOC( binomFixed, theta=seq( -.10,-.05,by=.01) )

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#####	Re-design trial with 1700 patients (850/arm)
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binomFixed.1700 <- update( binomFixed, sample.size=1700, power="calculate" )
binomFixed.1700

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#####	Inference on the boundary for re-designed trial
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seqInference( binomFixed.1700 )

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#####	Determine 80% power point fo re-designed trial
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seqOC( binomFixed.1700, power=.80 )

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#####	Compare power curve for re-designed trial
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seqPlotPower( binomFixed, binomFixed.1700, dsnLbls=c("N=2495","N=1700") )
seqPlotPower( binomFixed.1700, reference=binomFixed )


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#####	Sensitivity to baseline event rate
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Fixed.3 <- binomFixed.1700
Fixed.4 <- update( Fixed.3, null.hypothesis=.4, alt.hypothesis=.35 )
Fixed.2 <- update( Fixed.3, null.hypothesis=.2, alt.hypothesis=.15 )

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#####	Compare power at different baseline event rates
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seqPlotPower( Fixed.3, Fixed.2, Fixed.4, dsnLbls=c("Baseline Rate=.30", "Baseline Rate=.20", "Baseline Rate=.40") )
seqPlotPower( Fixed.2, Fixed.4, reference=Fixed.3, dsnLbls=c("Baseline Rate=.20", "Baseline Rate=.40") )


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#####
#####	Hodgkin's lymphoma trial
#####
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#####	Specification of inital fixed sample design
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survFixed <- seqDesign( prob.model = "hazard", arms = 2, null.hypothesis = 1., 
		alt.hypothesis = 0.67, ratio = c(1., 1.), nbr.analyses = 1, 
		test.type = "less", power = 0.80, alpha = 0.025 )
survFixed

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#####	Estimation of accrual rate
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seqPHSubjects( survFixed, controlMedian=0.75, accrualTime=3, followupTime=1 )

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#####	Evaluation of operating characteristics
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seqInference( survFixed )
seqOC(survFixed, theta=seq(.4,1,by=.05) )
seqPlotPower( survFixed, dsnLbls=c("survFixed"), lwd=2 )

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#####	Determine expected number of events if accrual were restricted to 50/mth
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seqPHSubjects( survFixed, controlMedian = 0.75, accrualTime = 3, followupTime = 1, nEvents = 121 )

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#####	Re-design trial with 121 maximal events
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survFixed.121 <- update( survFixed, sample.size=121, power="calculate" )
survFixed.121

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#####	Compare power curve for re-designed trial
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seqPlotPower( survFixed, survFixed.121, lwd=2 )
seqPlotPower( survFixed.121, reference=survFixed.196, lwd=2 )