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Confidence Interval After Trial Termination for Multi-Arm Multi-Stage Design

Source: R/RcppExports.R
getCI_mams.Rd

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

Usage

getCI_mams(
  M = NA_integer_,
  r = 1,
  corr_known = TRUE,
  L = NA_integer_,
  zL = NA_real_,
  IMax = NA_real_,
  informationRates = NA_real_,
  efficacyStopping = NA_integer_,
  criticalValues = NULL,
  alpha = 0.025,
  typeAlphaSpending = "sfOF",
  parameterAlphaSpending = NA_real_,
  spendingTime = NA_real_
)

Arguments

M

Number of active treatment arms.

r

Randomization ratio of each active arm to the common control.

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 used.

L

The termination look.

zL

The vector of z-test statistics at the termination look.

IMax

Maximum information for any active arm versus the common control.

informationRates

The information rates up to look L.

efficacyStopping

Indicators of whether efficacy stopping is allowed at each stage up to look L. 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. 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. Defaults to 0.025.

typeAlphaSpending

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

spendingTime

The error spending time up to look L. Defaults to missing, in which case, it is the same as informationRates.

Value

A data frame with the following components:

  • 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 typeAlphaSpending is "OF", "P", "WT", or "none", then informationRates, efficacyStopping, and spendingTime must be of full length kMax, and informationRates and spendingTime 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

getCI_mams(
  L = 2, zL = c(2.075, 2.264),
  M = 2, r = 1, corr_known = FALSE,
  IMax = 300 / 4, informationRates = c(1/2, 1),
  alpha = 0.025, typeAlphaSpending = "sfOF")
#>   level index     pvalue  thetahat cilevel       lower     upper
#> 1     2     2 0.02407215 0.1979009    0.95 0.001703645 0.4874185
#> 2     1     1 0.01957636 0.2389415    0.95 0.011919328 0.4657280