pwepowereq {PWEALL}

Calculating the powers of various the test statistics for equivalence trials

Description

This will calculate the powers for the test statistics accouting for staggered entry, delayed treatment effect, treatment crossover and loss to follow-up.

Usage

pwepowereq(t=seq(0.1,3,by=0.5),uppermargin=1.3,lowermargin=1/uppermargin,
           alpha=0.05,taur=1.2,u=c(1/taur,1/taur),ut=c(taur/2,taur),pi1=0.5,
             rate11=c(1,0.5),rate21=rate11,rate31=c(0.7,0.4),
             rate41=rate21,rate51=rate21,ratec1=c(0.5,0.6),
             rate10=rate11,rate20=rate10,rate30=rate31,
             rate40=rate20,rate50=rate20,ratec0=c(0.6,0.5),
             tchange=c(0,1),type1=1,type0=1,
             rp21=0.5,rp20=0.5,eps=1.0e-2,veps=1.0e-2,
             epsbeta=1.0e-4,iterbeta=25,n=1000)

Arguments

t

a vector of time points at which power is calculated, t must be positive

uppermargin

the upper margin for the hazard ratio

lowermargin

the lower margin for the hazard ratio

alpha

type-1 error rate

taur

Recruitment time

u

Piecewise constant recuitment rate

ut

Recruitment intervals

pi1

Allocation probability for the treatment group

rate11

Hazard before crossover for the treatment group

rate21

Hazard after crossover for the treatment group

rate31

Hazard for time to crossover for the treatment group

rate41

Hazard after crossover for the treatment group for complex case

rate51

Hazard after crossover for the treatment group for complex case

ratec1

Hazard for time to censoring for the treatment group

rate10

Hazard before crossover for the control group

rate20

Hazard after crossover for the control group

rate30

Hazard for time to crossover for the control group

rate40

Hazard after crossover for the control group for complex case

rate50

Hazard after crossover for the control group for complex case

ratec0

Hazard for time to censoring for the control group

tchange

A strictly increasing sequence of time points at which the event rates changes. The first element of tchange must be zero. It must have the same length as rate11, rate21, rate31, etc.

type1

Type of crossover in the treatment group

type0

Type of crossover in the control group

rp21

re-randomization prob in the treatment group

rp20

re-randomization prob in the control group

eps

error tolerence

veps

error tolenrence for calculating variance

epsbeta

error tolerance for calculating overall log HR

iterbeta

maximum number of iterations for calculating overall log HR

n

total number of subjects

Details

The hazard functions corresponding to rate11,...,rate51,ratec1, rate10,...,rate50,ratec0 are all piecewise constant function taking the form \lambda(t)=\sum_{j=1}^m \lambda_j I(t_{j-1}\le t<t_j), where \lambda_1,\ldots,\lambda_m are the corresponding elements of the rates and t_0,\ldots,t_{m-1} are the corresponding elements of tchange, t_m=\infty. Note that all the rates must have the same tchange.

Value

power

powers for cox model. First column is the more accurate power, second column is the power assuming the Fisher information equal to the varaince of beta

Note

Version 1.0 (7/19/2016)

Author(s)

Xiaodong Luo

References

Luo, et al. (2017)

See Also

pwe,rpwe,qpwe,ovbeta,innervar, pwepower,pwepowerni

Examples

t<-seq(3,6,by=1)
taur<-1.2
u<-c(1/taur,1/taur)
ut<-c(taur/2,taur)
r11<-c(0.2,0.1)
r21<-r11
r31<-c(0.03,0.02)
r41<-r51<-r21
rc1<-c(0.01,0.02)
r10<-c(0.2,0.2)
r20<-r10
r30<-c(0.02,0.01)
r40<-r50<-r20
rc0<-c(0.02,0.01)
getpowereq<-pwepowereq(t=t,uppermargin=1.3,lowermargin=0.8,alpha=0.05,taur=taur,
            u=u,ut=ut,pi1=0.5,rate11=r11,rate21=r21,rate31=r31,
            rate41=r41,rate51=r51,ratec1=rc1,
            rate10=r10,rate20=r20,rate30=r30,rate40=r40,rate50=r50,ratec0=rc0,
            tchange=c(0,1),type1=1,type0=1,n=1000)
###powers at each time point
cbind(t,getpowereq$power[,1:3])