Statistics for Traders #50: Newcombe (1998c) paired-differences CI — Method 10 (Wilson-based, continuity-corrected φ) applied to today's paired 9-print RBA sample comparing AUDNZD (0/9 UP at 15m) vs GBPAUD (9/9 UP). Cell counts e=0, f=0, g=9, h=0. δ̂ = -1.0. Method 10 gives CI [-1, -0.402]; paired Wald (method 1) collapses to a zero-width tethering aberration; Wald+CC (method 2) overshoots [-1, +1] at [-1.111, -0.889]. McNemar exact two-sided p = 1/128 = 0.0039. Closes the queued-since-2026-09-15 companion to Newcombe 1998a (Stats/PT #46). Same-day pairing with PT #50 (Newcombe 1998c primary source).
Newcombe (1998c) is the paired-data companion to Stats #46’s seven single-proportion methods. Method 10 is the Wilson-based CI on δ = p1 - p2 for paired binomial data. Applied to today’s AUDNZD vs GBPAUD 15m up-rate on the SAME 9 RBA small_miss print dates: cell counts e=0, f=0, g=9, h=0, δ̂ = -1.0. The naive paired Wald collapses to a zero-width interval AT -1 — the leading tethering aberrationNewcombe’s paper addresses. Method 10 (φ̂ = 0 because 3 of 4 cells are empty) gives 95% CI [-1, -0.402] — a proper interval that excludes zero. McNemar exact two-sided p = 1/128 = 0.0039.
![Horizontal bar chart showing four 95% confidence intervals on the paired difference δ = p1 - p2 for the AUDNZD vs GBPAUD 15m up-rate on 9 RBA small_miss print dates. Data: e=0, f=0, g=9, h=0 (all 9 pairs discordant favoring GBPAUD > AUDNZD). Method 1 Wald: zero-width interval tethered at -1 (labelled 'zero-width, tethered'). Method 2 Wald with continuity correction: [-1.111, -0.889] — overshoots the valid range [-1, +1] on both ends. Method 3 exact conditional: [-1, -0.664]. Method 10 Wilson-based (highlighted in green): [-1, -0.402]. Point estimate δ̂ = -1.0 marked. Vertical coral line at δ=0 shows all four intervals exclude the null.](/insights/stats-for-traders-newcombe-1998c-paired/method10-vs-wald.png)
Setup — Newcombe’s e/f/g/h notation on today’s data
Two paired outcomes on the same 9 subjects (each subject is one of the 9 RBA small_miss print dates): Y1 = “AUDNZD moves UP at 15m”, Y2 = “GBPAUD moves UP at 15m”. Newcombe’s 2x2 cell notation puts the four possible joint outcomes into cells e (both fail), f (Y1 succeeds, Y2 fails), g (Y1 fails, Y2 succeeds), h (both succeed).
| Cell | Meaning | Count |
|---|---|---|
| e | AUDNZD DOWN + GBPAUD DOWN (both fail) | 0 |
| f | AUDNZD UP + GBPAUD DOWN (Y1 wins) | 0 |
| g | AUDNZD DOWN + GBPAUD UP (Y2 wins) | 9 |
| h | AUDNZD UP + GBPAUD UP (both succeed) | 0 |
n = 9, δ̂ = (f - g)/n = -9/9 = -1.0(as extreme as possible on [-1, +1]). All 9 pairs are discordant, all favor GBPAUD > AUDNZD. p̂₁ = (h+f)/n = 0/9; p̂₂ = (h+g)/n = 9/9.
Wilson intervals for the two marginals, then method 10 combined CI
Method 10 works in two steps. First: compute the Wilson score CI (Stats #42) for each marginal proportion separately. Second: combine them with a paired-correlation adjustment φ̂. For our data three of four cells are zero, so Newcombe (§4) prescribes substituting φ̂ = 0.
| Quantity | Formula | Value |
|---|---|---|
| p̂₁ (AUDNZD UP rate) | (h + f)/n = 0/9 | 0.00000 |
| p̂₂ (GBPAUD UP rate) | (h + g)/n = 9/9 | 1.00000 |
| Wilson CI for p₁ | score interval, α=0.05 | [0, 0.29915] |
| Wilson CI for p₂ | score interval, α=0.05 | [0.70085, 1] |
| δ̂ = p̂₁ - p̂₂ | = (f - g)/n = -9/9 | -1.00000 |
| φ̂ (correlation, cc'd) | 0 (3 of 4 cells empty, §4) | 0 |
| L(δ) = L₁ - U₂ | with φ̂ = 0 | 0 - 1 = -1 (tethered) |
| U(δ) = U₁ - L₂ | with φ̂ = 0 | 0.29915 - 0.70085 = -0.40170 |
95% Newcombe method 10 CI on δ: [-1, -0.402]. The interval excludes 0 — REJECTS the null of equal paired proportions at 5%. Point estimate is at the boundary but the upper endpoint is genuinely interior (not tethered), unlike the Wald method below.
Failure mode 1 — paired Wald (method 1) zero-width aberration
The paired Wald SE is se = √(f + g - (f-g)²/n) / n. Plug in f=0, g=9, n=9: se = √(9 - 81/9) / 9 = √0 / 9 = 0. The Wald CI collapses to [-1, -1]— a zero-width interval tethered to the boundary. Newcombe (1998c §5) explicitly calls this a “tethering aberration” and uses it as the leading motivating failure for methods 5-10. A trader reading this interval would conclude “we’re CERTAIN δ = -1 exactly” — clearly wrong for n = 9.
Failure mode 2 — Wald with continuity correction (method 2)
Adding a Yates 1/n continuity correction to the Wald SE gives method 2: δ̂ ± (z·se + 1/n) = -1 ± 0.1111 = [-1.111, -0.889]. The interval now has width but OVERSHOOTS the valid range [-1, +1] on the lower endpoint (and would overshoot on the upper if δ̂ were positive). Newcombe Table II asterisks method 2 as an overshoot aberration for exactly this reason.
McNemar exact — same conclusion, no effect-size info
The classical significance test for paired binomial data is McNemar. Under H0: “P(discordant favors Y1) = 0.5”, the number of discordant pairs favoring Y1 is Binomial(9, 0.5). Observed = 0. One-sided p = 0.5⁹ = 1/512 = 0.00195; two-sided p = 2 × 0.5⁹ = 1/128 = 0.00391. Rejects H0 at 5%. But McNemar returns only a p-value; Newcombe method 10 also returns an EFFECT-SIZE interval (“δ ∈ [-1, -0.402] means AUDNZD’s up-rate is at least 40.2 percentage points below GBPAUD’s”) that the test alone lacks.
Comparison with slot 1’s Fisher’s exact
Slot 1 today used Fisher’s exact test (Stats #45) on the AUDNZD tail-vs-tail 2x2 [[9,0],[0,9]]: one-sided p = 1/C(18,9) = 1/48620 = 2.06e-5. That test compares TWO DIFFERENT SETS of prints (9 dovish surprises vs 9 hawkish surprises) — unpaired. Today’s Stats #50 compares the SAME 9 print dates measured on two different pairs — paired. Two different questions, two different tests, both reject the null at 5%. The paired p is 189x LESS extreme (0.0039 vs 2.06e-5) because pairing CONDITIONS on the discordant total (9) rather than the joint marginals (9,9;9,9), which throws away information about the overall rates that Fisher’s exact keeps.
Queue status
Closes “Newcombe’s paired-differences companion Statistics in Medicine 17:2635-2650” queued 2026-09-15 during PT #46 verification. Same-day pairing with today’s PT #50 Newcombe 1998c primary source. Cross-verified against scipy.stats.fisher_exact, scipy.stats.binom, and independent scipy 1.17.1 Wilson-score implementation on 2026-09-19. Queue rotates to Newcombe 1998b unpaired-difference eleven methods (Stats in Med 17:873-890, natural sibling completing the trilogy), He-Krishnamurthy 2013 (queued since PT #35), suppressor-variable partial-vs-semi-partial (queued since Stats #25), higher-order VAR-b prewhitening (queued since Stats #20). Chart via one-off script reusing embedded svg + sharp; not committed under scripts/.