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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 1/2, equal to the original budget. In the normal model, for any fixed critical value c>0, the equal-weight inverse-normal rule rejecting when (Z1+Z2)/2≥c has size α=∫c∞ϕ(t) dt∈(0,1/2). Choosing unit-norm weights from the sign of the interim statistic Z1 and retaining c raises that probability to 3α/2.

Facts & Assumptions

Given: AC; a finite uniform null probability space for the first model; independent fair binary coordinates I,B0,B2,B3; and, for the second model, independent standard-normal variables Z1,Z2 with density ϕ(x)=Ce−x2/2, where C=(∫Re−t2/2 dt)−1. Thus ϕ is even, continuous, strictly positive, and has total mass one. Write Φ(x)=∫−∞xϕ(t) dt.

[A1]

AC supplies the conditional-expectation classes inherited by the results used here. The Axiom of Choice

[F1]

For a countable-valued interim-measurable N, calibration within every selected-size stratum implies conditional superuniformity of the selected p-value. Selected-size conditional validity yields a conditionally superuniform p-value

[F2]

If a stage-2 p-value is conditionally superuniform given F1, rejection at the original conditional error A has conditional rejection probability at most A; when P0(R0)≤α, its overall null rejection probability is at most α. A conditionally superuniform stage-2 p-value preserves conditional error

[F3]

A p-value statistic is measurable, takes values in [0,1], and is valid under the null when its null CDF is superuniform. Valid p-values

[F4]

If an integrable variable is independent of F1, its conditional expectation given F1 is its ordinary expectation (under AC). Conditioning a known variable and an independent variable

[F5]

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.

1.1A1F1F2F3F4F5givenconstructalgebra

Put Ω={0,1}4 with the uniform law and let I,B0,B2,B3 be the independent fair-bit coordinates. Define pj=1/2 when Bj=0 and pj=1 when Bj=1, for j∈{0,2,3}. Each pj is measurable with values in [0,1], and its null CDF is 0 for u<1/2, 1/2 for 1/2≤u<1, and 1 at u=1, so each is a valid p-value by [F3]. Let F1=σ(I), select N=2 on I=0 and N=3 on I=1, and take the original rejection event R0={p0≤1/2}. Independence and [A1, F4] give its conditional error A=E0[1R0∣F1]=1/2 almost surely; [F5] makes the resulting event probabilities version-independent. For each m∈{2,3} and H∈F1, independence of Bm from I gives P0(H∩{N=m}∩{pN≤u})=c(u)P0(H∩{N=m}), where c(u)=0 for u<1/2, 1/2 for 1/2≤u<1, and 1 for u=1; in every case c(u)≤u. Thus [F1] makes pN conditionally superuniform. Rejection at A=1/2 is exactly the event that the selected bit is zero. Since P0(R0)=P0(B0=0)=1/2, set α=1/2 in the overall conclusion of [F2] to obtain P0(pN≤A)≤1/2; the selected bit is fair, so equality holds and the original budget is attained.

1.2F3givenconstructalgebra

The positive density makes Φ continuous and strictly increasing. Define the one-sided stage p-values pi=1−Φ(Zi), so Zi=Φ−1(1−pi); for 0<u<1, P0(pi≤u)=P0(Zi≥Φ−1(1−u))=u, and the endpoint inequalities are immediate, so they are valid by [F3]. Fix c>0 and set α=∫c∞ϕ(t) dt, with 0<α<1/2 by positivity and evenness. Under the fixed equal-weight inverse-normal rule, reject when W=(Z1+Z2)/2≥c. The orthogonal change of variables w=(z1+z2)/2, v=(z1−z2)/2 has absolute Jacobian 1 and satisfies z12+z22=w2+v2, so the joint density transforms to ϕ(w)ϕ(v) and integration over w≥c gives the fixed-rule null rejection probability α.

2.1givenstep 1.2constructalgebra∎

Choose N2=1 when Z1≥0 and N2=2 when Z1<0. Without recalibrating c, use weights w(N2)=(1,0) in the first case and (0,1) in the second; each has squared norm one. Since c>0, the adapted rejection event is the disjoint union {Z1≥c}∪{Z1<0,Z2≥c}, whose probability by independence is α+(1/2)α=3α/2>α. 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.

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