Type: | Package |
Title: | Group Sequential Refined Secondary Boundary |
Version: | 1.2.1 |
Description: | A gate-keeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Computations related to group sequential primary and secondary boundaries. Refined secondary boundaries are calculated for a gate-keeping test on a primary and a secondary endpoint in a group sequential design with multiple interim looks. The choices include both the standard boundaries and the boundaries using error spending functions. See Tamhane et al. (2018), "A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks", Biometrics, 74(1), 40-48. |
License: | GPL-3 |
Encoding: | UTF-8 |
Depends: | R (≥ 4.2.0) |
Imports: | stats (≥ 4.0.0), mvtnorm (≥ 1.1.0), ldbounds (≥ 2.0.0), xtable (≥ 1.8.0) |
RoxygenNote: | 7.2.3 |
NeedsCompilation: | no |
Packaged: | 2023-07-01 21:02:30 UTC; psystat |
Author: | Jiangtao Gou [cre, aut], Fengqing (Zoe) Zhang [aut] |
Maintainer: | Jiangtao Gou <gouRpackage@gmail.com> |
Repository: | CRAN |
Date/Publication: | 2023-07-04 13:00:05 UTC |
Lower and Upper Bounds Generator
Description
Generate lower and upper bounds for programs calculating the secondary endpoint's type I error when the correlation rho between the primary endpoint and the secondary endpoint equals 1.
Usage
cdBoundary(cvec, dvec, gammaVec, dlt, upper = TRUE)
Arguments
cvec |
primary boundary. |
dvec |
secondary boundary. |
gammaVec |
square root of information vector. |
dlt |
test statistic of the primary endpoint follows a normal distribution with mean |
upper |
type of bounds, upper bound is |
Details
This function generates upper and lower bounds for further computation. For more details, refer to Tamhane et al. (2018, Biometrics), section 4.2.
Value
lower and upper bounds for programs calculating the secondary endpoint's type I error when the correlation rho is 1.
Author(s)
Jiangtao Gou
References
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74(1), 40-48. Gou, J. (2022). Sample size optimization and initial allocation of the significance levels in group sequential trials with multiple endpoints. Biometrical Journal, 64(2), 301–311.
Examples
cvec <- rep(1.992,3)
dvec <- c(1.535*sqrt(3),1.535*sqrt(3/2),1.535)
gammaVec <- c(sqrt(1/3),sqrt(2/3),1)
dlt <- 2
uBoundary <- cdBoundary(cvec, dvec, gammaVec, dlt, upper=TRUE)
Correlation Matrix Generator
Description
Generate correlation matrix between standardized sample mean test statistics for the two endpoint at different looks.
Usage
genCorrMat(gammaVec, type, rhoPS = 0)
Arguments
gammaVec |
a vector which contains gamma_(1), ..., gamma_(K-1), gamma_(K), square root of information vector. |
type |
type of primary or secondary endpoint. For primary endpoint calculation, |
rhoPS |
correlation between primary and secondary endpoints. |
Details
This function generates correlation matrix between different mean statistics. For more details, refer to Tamhane et al. (2018, Biometrics), section 2.
Value
correlation matrix, K by K for primary endpoint, (K+1) by (K+1) for secondary endpoint, where K is the number of interims.
Author(s)
Jiangtao Gou
Fengqing (Zoe) Zhang
References
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74(1), 40-48. Tamhane, A. C., & Gou, J. (2022). Chapter 2 - Multiple test procedures based on p-values. In X. Cui, T. Dickhaus, Y. Ding, & J. C. Hsu (Eds.), Handbook of multiple comparisons (Vol. 45, pp. 11–34).
Examples
corrMat <- genCorrMat(gammaVec=c(sqrt(1/3), sqrt(2/3), 1), type=2, rhoPS = 0.3)
Find the Location of Maximum, Standard OBF and POC
Description
Calculate the location of maximal tyep I error of the standard O'Brien-Fleming and Pocock refined secondary boundaries.
Usage
initLocPeak(alpha, tVec, cvec, type = 2, initIntvl = c(1, 4))
Arguments
alpha |
type I error. |
tVec |
information vector. |
cvec |
primary group sequential boundary. |
type |
type of the test procedure for the secondary endpoint. O'Brien- Fleming (OBF) type error spending funciton is 1, Pocock (POC) type error spending funciton is 2. |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function search the location of the maximal point, in order to calculate the standard (origiinal) O'Brien-Fleming (OBF) and Pocock (POC) refined secondary boundaries.
Value
location of maximum, a number between 1 and the number of interims
Author(s)
Jiangtao Gou
References
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, to appear.
See Also
SecondaryBoundary
, ldInitLocBeak
Examples
require(mvtnorm)
K <- 8
gammaVec <- sqrt((1:K)/K)
tVec <- gammaVec^2
alpha <- 0.025
c <- 2.072274
cvec <- c/gammaVec
loc <- initLocPeak(alpha,tVec,cvec,type=2,initIntvl=c(1,3))
Find the Location of Maximum, Error Spending Approach
Description
Calculate the location of maximal type I error of secondary endpoint.
Usage
ldInitLocPeak(alpha, tVec, cvec, type = 2, initIntvl = c(0.8, 4))
Arguments
alpha |
type I error. |
tVec |
information vector. |
cvec |
primary group sequential boundary. |
type |
type of the test procedure for the secondary endpoint. O'Brien- Fleming (OBF) type error spending funciton is 1, Pocock (POC) type error spending funciton is 2. |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function searches the location of maximal type I error of secondary endpoint by using the error spending approach.
Value
location of maximum, a number between 1 and the number of interims.
Author(s)
Jiangtao Gou
References
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
ldSecondaryBoundary
, initLocBeak
Examples
## Not run:
require(mvtnorm)
require(ldbounds)
K <- 6;
tVec <- c(140,328,453,578,659,1080)/1080;
alpha = 0.025;
cvec.obf <- ldbounds::ldBounds(tVec,iuse=c(1),alpha=c(alpha),sides=1);
cvec <- cvec.obf$upper.bounds;
loc <- ldInitLocPeak(alpha,tVec,cvec,type=2,initIntvl=c(0.9,4))
## End(Not run)
Calculate Nominal Significance, Error Spending Approach
Description
Nominal significance for the secondary endpoint are calculated by using the error spending approach.
Usage
ldNominalSig(alpha, tVec, cvec, locPeak, type = 2, initIntvl = c(1, 4))
Arguments
alpha |
original significance level. |
tVec |
information vector. |
cvec |
primary group sequential boundary. |
locPeak |
location of maximum, a number between 1 and the number of interims. |
type |
O'Brien- Fleming (OBF) type error spending funciton is 1, Pocock (POC) type error spending funciton is 2. |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function calculates the nominal significance level of any Lan-DeMets error spending boundary. The original significance level is used to choose the initial searching range of the nominal significance.
Value
nominal significance of the secondary group sequential boundary.
Author(s)
Jiangtao Gou
References
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
nominalSig
, secondaryBoundaryVecLD
Examples
## Not run:
require(mvtnorm)
require(ldbounds)
K <- 6;
tVec <- c(140,328,453,578,659,1080)/1080;
alpha <- 0.025;
cvec.obf <- ldbounds::ldBounds(t=tVec,iuse=c(1),alpha=c(alpha),sides = 1);
cvec <- cvec.obf$upper.bounds;
alphaprime <- ldNominalSig(alpha,tVec,cvec,locPeak=4,type=2,
initIntvl=c(1,4))
## End(Not run)
Calculate Primary Boundaries, the Error Spending Approach
Description
Primary boundaries calculation of Lan-DeMets OBF and POC.
Usage
ldPrimaryBoundary(tVec, alpha, type = 1, initIntvl = c(0.8, 8))
Arguments
tVec |
a vector of information, gammaVec = sqrt(tVec). |
alpha |
significance level |
type |
type of sequential procedure. OBF is 1, POC is 2. |
initIntvl |
paramter for function uniroot (two numbers) |
Value
a vector of primary boundaries.
Author(s)
Jiangtao Gou
References
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74(1), 40-48.
Gou, J. (2023). Trigger strategy in repeated tests on multiple hypotheses. Statistics in Biopharmaceutical Research, 15(1), 133–140.
See Also
primaryBoundary
Difference between the Error Rate and Significance Level, the Error Spending Approach
Description
Calculate the difference between the error rate and significance level for the secondary endpoint, Lan-DeMets error spending approach.
Usage
ldSecControl(ap, alpha, cvec, tVec, ExtrmLoc, type = 2)
Arguments
ap |
significance level for the primary endpoint |
alpha |
targeted significance level for the secondary endpoint |
cvec |
a vector of calculated primary boundaries |
tVec |
a vector of information, gammaVec = sqrt(tVec) |
ExtrmLoc |
an integer between 1 and K, locate the maximum of type I error of secondary endpoint |
type |
type of sequential procedures. Type 1 OBF d, Type 2 POC d. |
Value
difference between alpha and the calculated error rate.
Author(s)
Jiangtao Gou
References
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74(1), 40-48.
See Also
secControl
Calculate Refined Secondary Boundary, Error Spending Approach
Description
Refined secondary boundaries are calculated by using the error spending approach.
Usage
ldSecondaryBoundary(
alpha,
tVec,
cvec,
locPeak,
type = 2,
initIntvl = c(0.6, 4)
)
Arguments
alpha |
original significance level. |
tVec |
information vector. |
cvec |
primary group sequential boundary. |
locPeak |
location of maximum, a number between 1 and the number of interims. |
type |
type of the test procedure for the secondary endpoint. O'Brien- Fleming (OBF) type error spending funciton is 1, Pocock (POC) type error spending funciton is 2. |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function calculates the refined secondary boundaries of any Lan-DeMets error spending boundary based on the primary boundaries.
Value
refined secondary boundaries.
Author(s)
Jiangtao Gou
References
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2017+). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
secondaryBoundary
, secondaryBoundaryVecLD
Examples
## Not run:
require(mvtnorm)
require(ldbounds)
K <- 6;
tVec <- c(140,328,453,578,659,1080)/1080;
alpha = 0.025;
cvec.obf <- ldbounds::ldBounds(t=tVec,iuse=c(1),alpha=c(alpha),sides = 1);
cvec <- cvec.obf$upper.bounds;
secbound <- ldSecondaryBoundary(alpha,tVec,cvec,locPeak=4,type=2,
initIntvl=c(0.8,8))
## End(Not run)
Calculate Nominal Significance, Standard Approach
Description
Nominal significance for the secondary endpoint are calculated by using the standard (original) approach.
Usage
nominalSig(gammaVec, cvec)
Arguments
gammaVec |
square root of information. |
cvec |
group sequential boundary. |
Details
This function calculates he nominal significance level of any given boundary.
Value
nominal significance
Author(s)
Jiangtao Gou
References
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
ldNominalSig
, secondaryBoundaryVecOrig
Examples
require(mvtnorm)
require(ldbounds)
nSig <- nominalSig(gammaVec=c(sqrt(1/3),1),cvec=c(2.2,1.8))
Calculate Primary Boundaries, Standard Approach
Description
Primary boundaries calculation of standard (original) OBF and POC.
Usage
primaryBoundary(gammaVec, alpha, type = 1, initIntvl = c(1, 4))
Arguments
gammaVec |
a vector of square root of information. |
alpha |
significance level |
type |
type of sequential procedure. OBF is 1, POC is 2. |
initIntvl |
paramter for function uniroot (two numbers) |
Value
original OBF and POC boundaries (primary endpoints) (a number, c_(K)).
Author(s)
Jiangtao Gou
References
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2017+). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, to appear.
See Also
ldPrimaryBoundary
Calculate the Primary Boundaries
Description
Primary boundaries are calculated, including the standard approach and the error spending approach.
Usage
primaryBoundaryVec(
alpha,
tVec,
OBF = TRUE,
LanDeMets = FALSE,
digits = 2,
printOut = TRUE,
initIntvl = c(1, 8)
)
Arguments
alpha |
significance level for the primary endpoint. |
tVec |
information (vector). |
OBF |
type of procedures. |
LanDeMets |
type of procedures. |
digits |
number of digits for output, |
printOut |
|
initIntvl |
parameter for function uniroot (two numbers) for function primaryBoundary or function ldPrimaryBoundary |
Value
OBF and POC boundaries (primary endpoints) (vector).
Author(s)
Jiangtao Gou
References
Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC, New York.
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74(1), 40-48.
Examples
require(mvtnorm)
K <- 4
alpha <- 0.025
tVec <- (1:K)/K
boundaryVector <- primaryBoundaryVec(alpha,tVec,initIntvl=c(1,4),
OBF=TRUE,LanDeMets=FALSE,digits=3,printOut=TRUE)
boundaryVector <- primaryBoundaryVec(alpha,tVec,initIntvl=c(1,4),
OBF=FALSE,LanDeMets=FALSE,digits=3,printOut=TRUE)
boundaryVector <- primaryBoundaryVec(alpha,tVec,initIntvl=c(1,8),
OBF=TRUE,LanDeMets=TRUE,digits=3,printOut=TRUE)
boundaryVector <- primaryBoundaryVec(alpha,tVec,initIntvl=c(1,4),
OBF=FALSE,LanDeMets=TRUE,digits=3,printOut=TRUE)
Summarize Primary and Refined Secondary Boundaries in a TeX table
Description
Primary boundaries and refined secondary boundaries are listed in a TeX table.
Usage
psbTeXtable(
alpha,
tVec,
pOBF = TRUE,
sOBF = FALSE,
LanDeMets = FALSE,
digits = 2
)
Arguments
alpha |
type I error probability. |
tVec |
vector of relative information levels. The last element in the vector is 1. |
pOBF |
type of primary boundary, |
sOBF |
type of secondary boundary, |
LanDeMets |
type of boundary, |
digits |
number of digits after decimal point to display in the table. |
Details
This function gives a TeX format table including both primary boundary and refined secondary boundary.
The number of digits after decimal point can be specified through parameter digits
.
Value
a TeX format table including both primary boundary and refined secondary boundary.
Author(s)
Jiangtao Gou
Fengqing (Zoe) Zhang
References
Glimm, E., Maurer, W., and Bretz, F. (2010). Hierarchical testing of multiple endpoints in group-sequential trials. Statistics in Medicine 29, 219-228.
Hung, H. M. J., Wang, S.-J., and O'Neill, R. (2007). Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials. Journal of Biopharmaceutical Statistics 17, 1201-1210.
Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC, New York.
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Mehta, C. R., and Liu, L. (2010). Testing a primary and a secondary endpoint in a group sequential design. Biometrics 66, 1174-1184.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
Examples
require(mvtnorm)
require(ldbounds)
require(xtable)
psbTeXtable(alpha=0.025,tVec=c(1/2,3/4,1),pOBF=TRUE,sOBF=FALSE,LanDeMets=FALSE)
Summarize Primary and Refined Secondary Boundaries, Nominal Significance
Description
Primary boundaries, refined secondary boundaries, and nominal significance for the secondary endpoint are listed.
Usage
refinedBoundary(
alpha,
tVec,
pOBF = TRUE,
sOBF = FALSE,
LanDeMets = FALSE,
digits = 2
)
Arguments
alpha |
type I error probability. |
tVec |
vector of relative information levels. The last element in the vector is 1. |
pOBF |
type of primary boundary, |
sOBF |
type of secondary boundary, |
LanDeMets |
type of boundary, |
digits |
number of digits after decimal point for primary and secondary boundaries. |
Details
This function gives a list including primary boundary, refined secondary boundary, and the nominal significance for the secondary endpoint.
The number of digits for the nominal significance depends on parameter alpha
.
Value
a result list including primary boundary, refined secondary boundary, and the nominal significance for the secondary endpoint.
Author(s)
Jiangtao Gou
References
Glimm, E., Maurer, W., and Bretz, F. (2010). Hierarchical testing of multiple endpoints in group-sequential trials. Statistics in Medicine 29, 219-228.
Hung, H. M. J., Wang, S.-J., and O'Neill, R. (2007). Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials. Journal of Biopharmaceutical Statistics 17, 1201-1210.
Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC, New York.
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Mehta, C. R., and Liu, L. (2010). Testing a primary and a secondary endpoint in a group sequential design. Biometrics 66, 1174-1184.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48
Examples
require(mvtnorm)
require(ldbounds)
result <- refinedBoundary(alpha=0.05,tVec=c(0.2,0.6,1))
result$primaryBoundary
result$secondaryBoundary
result$nomialSignificance
Difference between the Error Rate and Significance Level, Standard Approach
Description
Calculate the difference between the error rate and significance level for the secondary endpoint, standard (original) approach.
Usage
secControl(d, alpha, cvec, gammaVec, ExtrmLoc, type = 2)
Arguments
d |
boundary of secondary endpoint at the final look (a number, d_(K)) |
alpha |
targeted significance level for the secondary endpoint |
cvec |
a vector of calculated primary boundaries |
gammaVec |
square root of information |
ExtrmLoc |
an integer between 1 and K, locate the maximum of type I error of secondary endpoint |
type |
type of sequential procedures. Type 1 OBF d, Type 2 POC d. |
Value
difference between alpha and the calculated error rate.
Author(s)
Jiangtao Gou
References
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74(1), 40-48.
See Also
ldSecControl
Calculate the Refined Secondary Boundaries, Standard OBF and POC
Description
Calculate the standard O'Brien-Fleming and Pocock refined secondary boundaries
Usage
secondaryBoundary(alpha, tVec, cvec, locPeak, type = 2, initIntvl = c(1, 4))
Arguments
alpha |
type I error. |
tVec |
information vector. |
cvec |
primary group sequential boundary. |
locPeak |
location of maximum, a number between 1 and the number of interims. |
type |
type of the test procedure for the secondary endpoint. O'Brien- Fleming (OBF) type error spending funciton is 1, Pocock (POC) type error spending funciton is 2. |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function calculates the standard (origiinal) O'Brien-Fleming (OBF) and Pocock (POC) refined secondary boundaries.
Value
standard O'Brien-Fleming and Pocock refined secondary boundaries.
Author(s)
Jiangtao Gou
References
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2017+). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
ldSecondaryBoundary
, initLocBeak
Examples
## Not run:
require(mvtnorm)
K <- 8
gammaVec <- sqrt((1:K)/K)
tVec <- gammaVec^2
alpha = 0.025
c <- 2.072274
cvec <- c/gammaVec
loc <- initLocPeak(alpha,tVec,cvec,type=2,initIntvl=c(1,4))
sbvec <- secondaryBoundary(alpha,tVec,cvec,loc,type=2,
initIntvl=c(1,8))
## End(Not run)
Calculate Refined Secondary Boundaries and Nominal Significance
Description
Refined secondary boundaries, and nominal significance for the secondary endpoint are calculated.
Usage
secondaryBoundaryVec(
alpha,
tVec,
pOBF = TRUE,
sOBF = FALSE,
LanDeMets = FALSE,
initIntvl = c(0.8, 8)
)
Arguments
alpha |
type I error probability. |
tVec |
vector of relative information levels. The last element in the vector is 1. |
pOBF |
type of primary boundary, |
sOBF |
type of secondary boundary, |
LanDeMets |
type of boundary, |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function gives a list including refined secondary boundary and the nominal significance for the secondary endpoint.
There are a computing parameter initIntvl
.
Parameter initIntvl
contains the end-points of the interval to be searched for the root.
For Lan-DeMets error spending approach, the lower end point should choose a number slightly less than 1,
and the upper end point should choose a number between 4 and 10.
Value
a result list including refined secondary boundary and the nominal significance for the secondary endpoint.
Author(s)
Jiangtao Gou
References
Glimm, E., Maurer, W., and Bretz, F. (2010). Hierarchical testing of multiple endpoints in group-sequential trials. Statistics in Medicine 29, 219-228.
Hung, H. M. J., Wang, S.-J., and O'Neill, R. (2007). Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials. Journal of Biopharmaceutical Statistics 17, 1201-1210.
Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC, New York.
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Mehta, C. R., and Liu, L. (2010). Testing a primary and a secondary endpoint in a group sequential design. Biometrics 66, 1174-1184.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
secondaryBoundaryVecLD
, secondaryBoundaryVecOrig
Examples
require(mvtnorm)
require(ldbounds)
result <- secondaryBoundaryVec(alpha=0.025,tVec=c(1/2,1),pOBF=TRUE,sOBF=FALSE,
LanDeMets=FALSE,initIntvl=c(0.8,5))
result$secondaryBoundary
result$nomialSignificance
Calculate Refined Secondary Boundaries and Nominal Significance, the Error Spending Approach
Description
Lan-DeMets refined secondary boundaries, and nominal significance for the secondary endpoint are calculated by using the error spending approach.
Usage
secondaryBoundaryVecLD(
alpha,
tVec,
primaryOBF = TRUE,
secondaryOBF = FALSE,
initIntvl = c(0.8, 8)
)
Arguments
alpha |
type I error probability. |
tVec |
vector of relative information levels. The last element in the vector is 1. |
primaryOBF |
type of primary boundary, |
secondaryOBF |
type of secondary boundary, |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function uses the Lan-DeMets error spending approach,
and gives a list including refined secondary boundary and the nominal significance for the secondary endpoint.
There is a computing parameter initIntvl
.
Parameter initIntvl
contains the end-points of the interval to be searched for the root.
For Lan-DeMets error spending approach, the lower end point should choose a number slightly less than 1,
and the upper end point should choose a number between 4 and 10.
Value
a result list including Lan-DeMets refined secondary boundary and the nominal significance for the secondary endpoint.
Author(s)
Jiangtao Gou
References
Glimm, E., Maurer, W., and Bretz, F. (2010). Hierarchical testing of multiple endpoints in group-sequential trials. Statistics in Medicine 29, 219-228.
Hung, H. M. J., Wang, S.-J., and O'Neill, R. (2007). Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials. Journal of Biopharmaceutical Statistics 17, 1201-1210.
Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC, New York.
Lan, K. K. G., and Demets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Mehta, C. R., and Liu, L. (2010). Testing a primary and a secondary endpoint in a group sequential design. Biometrics 66, 1174-1184.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
secondaryBoundaryVec
, secondaryBoundaryVecOrig
Examples
require(mvtnorm)
require(ldbounds)
result <- secondaryBoundaryVecLD(alpha=0.025,tVec=c(1/2,1),primaryOBF=TRUE,
secondaryOBF=FALSE,initIntvl=c(0.8,6))
result$secondaryBoundary
result$nomialSignificance
Calculate Refined Secondary Boundaries and Nominal Significance, Standard Approach
Description
Standard refined secondary boundaries, and nominal significance for the secondary endpoint are calculated by using the standard (original) approach.
Usage
secondaryBoundaryVecOrig(
alpha,
tVec,
primaryOBF = TRUE,
secondaryOBF = FALSE,
initIntvl = c(1, 8)
)
Arguments
alpha |
type I error probability. |
tVec |
vector of relative information levels. The last element in the vector is 1. |
primaryOBF |
type of primary boundary, |
secondaryOBF |
type of secondary boundary, |
initIntvl |
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root. |
Details
This function uses the standard approach (O'Brien and Fleming 1979, Pocock 1977),
and gives a list including refined secondary boundary and the nominal significance for the secondary endpoint.
There is a computing parameter initIntvl
.
Parameter initIntvl
contains the end-points of the interval to be searched for the root.
The lower end point should choose a number around 1,
and the upper end point should choose a number between 4 and 10.
Value
a result list including standard refined secondary boundary and the nominal significance for the secondary endpoint.
Author(s)
Jiangtao Gou
References
Glimm, E., Maurer, W., and Bretz, F. (2010). Hierarchical testing of multiple endpoints in group-sequential trials. Statistics in Medicine 29, 219-228.
Hung, H. M. J., Wang, S.-J., and O'Neill, R. (2007). Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials. Journal of Biopharmaceutical Statistics 17, 1201-1210.
Jennison, C. and Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC, New York.
O'Brien, P. C., and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64, 191-199.
Tamhane, A. C., Mehta, C. R., and Liu, L. (2010). Testing a primary and a secondary endpoint in a group sequential design. Biometrics 66, 1174-1184.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2018). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, 74, 40-48.
See Also
secondaryBoundaryVec
, secondaryBoundaryVecLD
Examples
require(mvtnorm)
require(ldbounds)
result <- secondaryBoundaryVecOrig(alpha=0.025,tVec=c(1/2,1),primaryOBF=TRUE,
secondaryOBF=FALSE, initIntvl=c(1,4))
result$secondaryBoundary
result$nomialSignificance