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Calibrated selected sample size and an uncalibrated weight change
Statement
In the finite null model below, the selected stage-2 sample size is a function of interim information, and each selected-size p-value retains its conditional null calibration. The rejection rule at the original conditional error has null rejection probability , equal to the original budget. In the normal model, for any fixed critical value , the equal-weight inverse-normal rule rejecting when has size . Choosing unit-norm weights from the sign of the interim statistic and retaining raises that probability to .
Facts & Assumptions
Given: AC; a finite uniform null probability space for the first model; independent fair binary coordinates ; and, for the second model, independent standard-normal variables with density , where . Thus is even, continuous, strictly positive, and has total mass one. Write .
AC supplies the conditional-expectation classes inherited by the results used here. The Axiom of Choice
For a countable-valued interim-measurable , calibration within every selected-size stratum implies conditional superuniformity of the selected p-value. Selected-size conditional validity yields a conditionally superuniform p-value
If a stage-2 p-value is conditionally superuniform given , rejection at the original conditional error has conditional rejection probability at most ; when , its overall null rejection probability is at most . A conditionally superuniform stage-2 p-value preserves conditional error
A p-value statistic is measurable, takes values in , and is valid under the null when its null CDF is superuniform. Valid p-values
If an integrable variable is independent of , its conditional expectation given is its ordinary expectation (under AC). Conditioning a known variable and an independent variable
Conditional expectations are almost-sure classes, so changing a version does not alter event probabilities. Conditional expectation as an ae class
Verification
Given: The two null models and notation stated above; verify the calibrated finite-size rejection probability and the changed-weight normal rejection probability.
Put with the uniform law and let be the independent fair-bit coordinates. Define when and when , for . Each is measurable with values in , and its null CDF is for , for , and at , so each is a valid p-value by [F3]. Let , select on and on , and take the original rejection event . Independence and [A1, F4] give its conditional error almost surely; [F5] makes the resulting event probabilities version-independent. For each and , independence of from gives , where for , for , and for ; in every case . Thus [F1] makes conditionally superuniform. Rejection at is exactly the event that the selected bit is zero. Since , set in the overall conclusion of [F2] to obtain ; the selected bit is fair, so equality holds and the original budget is attained.
The positive density makes continuous and strictly increasing. Define the one-sided stage p-values , so ; for , , and the endpoint inequalities are immediate, so they are valid by [F3]. Fix and set , with by positivity and evenness. Under the fixed equal-weight inverse-normal rule, reject when . The orthogonal change of variables , has absolute Jacobian and satisfies , so the joint density transforms to and integration over gives the fixed-rule null rejection probability .
Choose when and when . Without recalibrating , use weights in the first case and in the second; each has squared norm one. Since , the adapted rejection event is the disjoint union , whose probability by independence is . Thus unit-norm weights selected with the stage-2 size do not by themselves preserve the fixed-rule error probability.
Remarks
The normal counterexample uses extreme weights so its size calculation is exact. Sugiura–Uesaka give the more direct sample-size-weight warning: in the weighted inverse-normal rule, replacing the prespecified second-stage size by its interim-selected value can exceed the target null rejection probability. The finite calibrated model above illustrates the separate condition that must be checked: the selected second-stage p-value law under the null.
Depends on
- Selected-size conditional validity yields a conditionally superuniform p-value
- A conditionally superuniform stage-2 p-value preserves conditional error
- Conditional expectation as an ae class
- The Axiom of Choice
- Probability measures and probability spaces
- Valid p-values
- Conditioning a known variable and an independent variable
Used by
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Sources
- Kenkichi Sugiura and Hiroyuki Uesaka, Theoretical Basis of Adaptive Designs for Clinical Trials in Phase II and III, Japanese Journal of Biometrics 29, Special Issue 1 (2008), S33–S52 (standard reference, not scraped)
- Giorgos Minas, Multivariate Global Testing and Adaptive Designs, PhD thesis, University of Warwick (2013) (standard reference, not scraped)