View source: R/pwecxpwufindt.R
pwecxpwufindt | R Documentation |
This will calculate the timeline from study inception accouting for staggered entry, delayed treatment effect, treatment crossover and loss to follow-up.
pwecxpwufindt(target=400,ntotal=1000,taur=5,u=c(1/taur,1/taur),ut=c(taur/2,taur),pi1=0.5,
rate11=c(1,0.5),rate21=c(0.8,0.9),rate31=c(0.7,0.4),
rate41=rate21,rate51=rate21,ratec1=c(0.5,0.6),
rate10=c(1,0.7),rate20=c(0.9,0.7),rate30=c(0.4,0.6),
rate40=rate20,rate50=rate20,ratec0=c(0.3,0.3),
tchange=c(0,1),type1=1,type0=1,
rp21=0.5,rp20=0.5,eps=1.0e-2,
init=taur,epsilon=0.000001,maxiter=100)
target |
target number of events |
ntotal |
total number of subjects |
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 |
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 |
A small number representing the error tolerance when calculating the utility function
with |
init |
initital value of the timeline estimate |
epsilon |
A small number representing the error tolerance when calculating the timeline. |
maxiter |
Maximum number of iterations when calculating the timeline |
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
.
t1 |
the calculated timeline |
tvar |
the true variance of the timeline estimator |
eps |
final tolerance |
iter |
Number of iterations performed |
Version 1.0 (7/19/2016)
Xiaodong Luo
Luo et al. (2018) Design and monitoring of survival trials in complex scenarios, Statistics in Medicine <doi: https://doi.org/10.1002/sim.7975>.
pwe
,rpwe
,qpwe
,instudyfindt
target<-400
ntotal<-2000
taur<-1.2
u<-c(1/taur,1/taur)
ut<-c(taur/2,taur)
r11<-c(1,0.5)
r21<-c(0.5,0.8)
r31<-c(0.7,0.4)
r41<-r51<-r21
rc1<-c(0.5,0.6)
r10<-c(1,0.7)
r20<-c(0.5,1)
r30<-c(0.3,0.4)
r40<-r50<-r20
rc0<-c(0.2,0.4)
gettimeline<-pwecxpwufindt(target=target,ntotal=ntotal,
taur=5,u=c(1/taur,1/taur),ut=c(taur/2,taur),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,eps=1.0e-2,init=taur,epsilon=0.000001,maxiter=100)
gettimeline$t1
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.