etsi (version 1.0)

etsi.main: Estimates the pooled treatment effect quantity, standard error, and corresponding p-value.

Description

Estimates the pooled treatment effect quantity in Study B, using the surrogate information learned from Study A. Provides the corresponding estimated standard error and p-value for testing the null hypothesis of a treatment effect equal to 0.

Usage

etsi.main(Study.A, Study.B, kappa = NULL)

Value

A list is returned:

delta.P

The pooled treatment effect quantity for Study B

se.delta.P

Standard error of delta.P

p.value

p-value for testing the null hypothesis that delta.P = 0

Arguments

Study.A

Study.A, a dataframe representing Study A containing the required columns A (treatment assignment), Y (primary outcome), S (surrogate outcome), and W (baseline covariate of interest). Optionally contains a column delta, which is an indicator for strong surrogacy.

Study.B

Study.B, a dataframe representing Study B containing the required columns A (treatment assignment), Y (primary outcome), S (surrogate outcome), and W (baseline covariate of interest). Optionally contains a column delta, which is an indicator for strong surrogacy.

kappa

kappa, the threshold to determine strong surrogacy when the delta columns are not provided in Study.A and Study.B. Surrogacy is considered sufficiently strong when the estimated PTE with respect to W is greater than kappa.

Author

Rebecca Knowlton

References

Knowlton, R., Parast, L. (2025) "Efficient Testing Using Surrogate Information." Biometrical Journal, 67(6): e70086.

Examples

  data(exampledataA)
  data(exampledataB)
  names(exampledataA)
  names(exampledataB)
  etsi.main(Study.A = exampledataA,
            Study.B = exampledataB)