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Confidence Interval After Adaptation for Multi-Arm Multi-Stage Design

Source: R/RcppExports.R
getADCI_mams.Rd

Obtains the p-value, conservative point estimate, and confidence interval after the end of an adaptive multi-arm multi-stage trial.

Usage

getADCI_mams(
  M = NA_integer_,
  r = 1,
  corr_known = TRUE,
  L = NA_integer_,
  zL = NA_real_,
  IMax = NA_real_,
  kMax = NA_integer_,
  informationRates = NA_real_,
  efficacyStopping = NA_integer_,
  criticalValues = NULL,
  alpha = 0.25,
  typeAlphaSpending = "sfOF",
  parameterAlphaSpending = NA_real_,
  spendingTime = NA_real_,
  MullerSchafer = FALSE,
  MNew = NA_integer_,
  selected = NA_integer_,
  rNew = 1,
  Lc = NA_integer_,
  zLc = NA_real_,
  INew = NA_real_,
  informationRatesNew = NA_real_,
  efficacyStoppingNew = NA_integer_,
  typeAlphaSpendingNew = "sfOF",
  parameterAlphaSpendingNew = NA_real_,
  spendingTimeNew = NA_real_
)

Arguments

M

Number of active treatment arms in the primary trial.

r

Randomization ratio of each active arm to the common control in the primary trial.

corr_known

Logical. If TRUE, the correlation between Wald statistics is derived from the randomization ratio \(r\) as \(r / (r + 1)\). If FALSE, a conservative correlation of 0 is assumed.

L

The interim adaptation look of the primary trial.

zL

The z-test statistics at the interim adaptation look of the primary trial.

IMax

Maximum information for any active arm versus the common control for the primary trial. Must be provided.

kMax

The maximum number of stages of the primary trial.

informationRates

The information rates of the primary trial.

efficacyStopping

Indicators of whether efficacy stopping is allowed at each stage of the primary trial. Defaults to TRUE if left unspecified.

criticalValues

The matrix of by-level upper boundaries on the max z-test statistic scale for efficacy stopping up to look L for the primary trial. The first column is for level M, the second column is for level M - 1, and so on, with the last column for level 1. If left unspecified, the critical values will be computed based on the specified alpha spending function.

alpha

The significance level of the primary trial. Defaults to 0.025.

typeAlphaSpending

The type of alpha spending for the primary trial. One of the following: "OF" for O'Brien-Fleming boundaries, "P" for Pocock boundaries, "WT" for Wang & Tsiatis boundaries, "sfOF" for O'Brien-Fleming type spending function, "sfP" for Pocock type spending function, "sfKD" for Kim & DeMets spending function, "sfHSD" for Hwang, Shi & DeCani spending function, and "none" for no early efficacy stopping. Defaults to "sfOF".

parameterAlphaSpending

The parameter value of alpha spending for the primary trial. Corresponds to \(\Delta\) for "WT", \(\rho\) for "sfKD", and \(\gamma\) for "sfHSD".

spendingTime

The error spending time of the primary trial. Defaults to missing, in which case, it is the same as informationRates.

MullerSchafer

Whether to use the Muller and Schafer (2001) method for trial adaptation.

MNew

The number of active treatment arms in the secondary trial.

selected

The indices of the selected treatment arms for the secondary trial among the M active arms in the primary trial.

rNew

The randomization ratio of each active arm to the common control in the secondary trial.

Lc

The termination look of the integrated trial.

zLc

The z-test statistics at the termination look of the integrated trial.

INew

The maximum information for any active arm versus the common control in the secondary trial.

informationRatesNew

The spacing of looks of the secondary trial.

efficacyStoppingNew

The indicators of whether efficacy stopping is allowed at each look of the secondary trial. Defaults to TRUE if left unspecified.

typeAlphaSpendingNew

The type of alpha spending for the secondary trial. One of the following: "OF" for O'Brien-Fleming boundaries, "sfOF" for O'Brien-Fleming type spending function, "sfP" for Pocock type spending function, "sfKD" for Kim & DeMets spending function, "sfHSD" for Hwang, Shi & DeCani spending function, and "none" for no early efficacy stopping. Defaults to "sfOF".

parameterAlphaSpendingNew

The parameter value of alpha spending for the secondary trial. Corresponds to \(\rho\) for "sfKD", and \(\gamma\) for "sfHSD".

spendingTimeNew

The error spending time of the secondary trial. Defaults to missing, in which case, it is the same as informationRatesNew.

Value

A data frame with the following variables:

  • level: Number of individual hypotheses considered for multiplicity.

  • index: The treatment arm with max Z among the active arms.

  • pvalue: p-value for rejecting the null hypothesis.

  • thetahat: Point estimate of the parameter.

  • cilevel: Confidence interval level.

  • lower: Lower bound of confidence interval.

  • upper: Upper bound of confidence interval.

Details

If typeAlphaSpendingNew is "OF" or "none", then informationRatesNew, efficacyStoppingNew, and spendingTimeNew must be of full length kNew, and informationRatesNew and spendingTimeNew must end with 1.

References

Ping Gao, Yingqiu Li. Adaptive multiple comparison sequential design (AMCSD) for clinical trials. Journal of Biopharmaceutical Statistics, 2024, 34(3), 424-440.

Author

Kaifeng Lu, kaifenglu@gmail.com

Examples

getADCI_mams(
  M = 2, r = 1, corr_known = FALSE, L = 1, zL = c(2.075, 2.264),
  IMax = 300 / 4, kMax = 2, informationRates = c(0.5, 1),
  alpha = 0.025, typeAlphaSpending = "sfOF",
  MNew = 1, selected = 2, rNew = 1,
  Lc = 2, zLc = 1.667, INew = 374 / 4)
#>   level index     pvalue  thetahat cilevel       lower     upper
#> 1     1     2 0.02551278 0.1712693    0.95 -0.00078926 0.3530049