Why Fisher's exact test is least exact where it matters most: achieved size, wasted power, and a routing rule for 2×2 tables William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22238930. This release (v1.1.14):10.5281/zenodo.22262453, published Sep 2, 2026; the concept DOI above resolves to it. The previous release, v1.1.13, is 10.5281/zenodo.22262451; earlier, v1.1.5 is 10.5281/zenodo.22260812 and v1.1.4 is 10.5281/zenodo.22260570. What this is The reproducibility deposit for the m02d paper. "Fisher's exact test" is exactly valid — its true rejection rate never exceeds the nominal α — but it is not size-exact: because the 2×2 reference distribution is discrete, no table boundary falls at α, so the achieved (unconditional) size sits below nominal. At small designs the test spends only 26–66% of its α budget, and wasted size is wasted power. The paper computes the achieved size, the wasted-power cost, and the significance-flip behaviour of Fisher's exact against a conservative→liberal roster (Yates χ², Fisher, mid-p, Boschloo, Barnard, Pearson χ², Cressie–Read λ=2/3, likelihood-ratio G), and distills the result into a routing rule for the 2×2. Everything is deterministic exhaustive enumeration — two independent binomials, no Monte Carlo, no random seed — so there is no simulation error: every number, table, and figure reproduces exactly from a named script. The keynote A real-data scan of 6,030 public 2×2 tables (757 pydataset/Rdatasets datasets) shows the tests agree essentially everywhere away from the threshold but disagreement spikes on each decision line — ~67% of tables within ±0.02 of 0.05 and ~76% within ±0.02 of the 0.10 trend line get a test-dependent verdict — so the tests are miscalibrated relative to one another exactly where we use them to draw the significant/not-significant line, and the trend line inherits the same spike. Flips are read on a three-tier taxonomy relative to Boschloo (the valid frontier): conservative below it, valid on it, liberal above it. What the deposit contains Manuscript (author + anonymized, .md), the Derivations companion (D1–D6: conditional validity and the achieved-size shortfall; mid-p as the mean of the median-unbiased rule with E₀[mid-p] = ½; Boschloo's uniform power dominance; the nesting that makes flips one-directional; the atom-lattice gap and exact Boschloo region behind Figure 3; and why conditioning forfeits the budget), the novelty / prior-art companion, and the cover letter(The American Statistician). Reproducibility apparatus (rerun/) — the exact-enumeration engine achieved_size.py (tie-aware conditional p-values, validated against SciPy to 2.2e-16) and the deterministic sweep drivers: power_and_flips.py, size_skew_sweep.py, flip_boundary_sweep.py, roster_sweep.py (the full comparator roster, including the Cressie–Read λ=2/3 power-divergence member), and public_flip_scan.py (the real-corpus scan). Each writes its locked JSON/CSV. Figures (figures/) — the achieved-size and wasted-power panels, the size×skew heat maps, the α=0.05 flip-boundary maps, the χ²-inclusive roster figures, the real-data flip-incidence figure, the routing flowchart (now Figure 9), and the per-test direction butterfly (Figure 8). Interactive demonstrator honest_fisher.html — a self-contained in-browser calculator with the full comparator taxonomy and the live-highlight routing flowchart; its JavaScript engine reproduces the deposited numbers and self-checks a parity badge on load. Deep-dive record (deepdives/) — the supporting analyses, including the size/skew, flip-boundary, χ²-roster, real-data, and computed-clearance write-ups, and the M0u-bundle assessment that reconciles m02d with the author's earlier Monte-Carlo program (below). LICENSE, CITATION.cff, MANIFEST.txt (SHA-256 of every file). The Cressie–Read λ=2/3 reconciliation The roster now carries Cressie–Read λ=2/3, the best-calibrated member of the power-divergence family that also contains Pearson (λ=1) and the G-test (λ=0). Across R×C shapes it is the best-calibrated test in the author's companion Monte-Carlo study; on the pure 2×2 that is m02d's subject, its exact achieved size is 0.062 / 0.053 / 0.055 / 0.055 at the representative designs — still mildly liberal, because small-sample discreteness bites it too. So the paper names λ=2/3 as the calibrated member of the χ² family, scopes the "common χ² defaults overshoot" claim to Pearson/Yates/G, and shows that even the well-chosen asymptotic statistic does not escape the 2×2 discreteness the exact unconditional tests handle — turning a potential referee objection into a strengthening of the routing rule. The companion 18-test Monte-Carlo study independently confirms m02d's Boschloo/Barnard power gap over Fisher (+3 to +10 pp by simulation vs +3.7 to +11.1 pp by exact enumeration here). All computation is deterministic exact enumeration; code is released under the MIT License, and text, figures, and data under CC BY 4.0. The public 2×2 corpus is built from the Rdatasets collection via pydataset; no data are redistributed beyond the illustrative tables cited in the paper. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). Why Fisher's exact test is least exact where it matters most: achieved size, wasted power, and a routing rule for 2×2 tables — reproducibility deposit [Software]. Zenodo.https://doi.org/10.5281/zenodo.22238930 BibTeX: bibtex @software{dwyer_m02d_2026, author = {Dwyer, William J.}, title = {Why Fisher's exact test is least exact where it matters most: achieved size, wasted power, and a routing rule for 2x2 tables --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.22238930}, url = {https://doi.org/10.5281/zenodo.22238930}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in its place. When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.1.14 — ✅ 10.5281/zenodo.22262453 (published 2026-09-02) (m02d_fishers_exact_not_exact_reproducibility_v1.1.14.zip, md5 4977e10c1b632054e3e6609176dde2fd, 3,722,698 B, 94 files): the Boschloo-dominates-Fisher machinery, made explicit. Section 6 now shows the one-line power-dominance mechanism rather than only asserting it: Fisher's own conditional test already has unconditional size ≤ α, so the calibrated Boschloo threshold c satisfies c ≥ α, and because both tests threshold the same statistic the rejection set {Fisher p ≤ α} sits inside {Fisher p ≤ c} table for table — Boschloo rejects wherever Fisher does and more, so it is uniformly at least as powerful, a guarantee that would fail for a differently-ordered unconditional statistic. Derivation D3.4 gains the explicit note that Boschloo and the score-based Barnard test are mutually non-nested (neither uniformly dominates; Barnard's occasional power edge is budget spent, not dominance), and the SN supplement gains a "Why Boschloo, not Barnard, is the valid frontier" note beside the comprehensive roster. Exposition over the existing exact-enumeration output; no computed result, figure, or table changed. Deterministic (identical md5 on two runs). Supersedes v1.1.13. v1.1.13 — ✅ 10.5281/zenodo.22262451 (published 2026-09-02) (m02d_fishers_exact_not_exact_reproducibility_v1.1.13.zip, md5 371a192f5a3ea8ad1e552043a3d68562, 3,721,908 B, 94 files): the comprehensive-roster and full-budget-grid build-out, and the worked-example correction. Adds the sixteen-statistic exact achieved-size-and-power engine comprehensive_roster.py, the full per-test α-budget-grid enginebudget_grid_all.py, the vectorized Boschloo helper boschloo_fast.py (an O(P·K) replacement for the O(n⁴) per-cell sup, verified cell-for-cell against the naive loop, which makes exact enumeration to n = 100 tractable), and the supplement table generator splice_supplement_tables.py. The SN supplement's per-test α-budget grids now run n = 6, 8, …, 20, 25, …, 65, 80, 100 and the big-tent size/power tables use the columns n = 8, 10, 16, 25, 40, 65, 100. Also corrects the worked-example Table S1 Cressie–Read λ = 2/3 value — the deposited 0.1881 ("not significant") was wrong; the exact statistic gives p = 0.0287 (significant), cross-checked against scipy.stats.power_divergence — expands that table to the full sixteen-test roster, and rewrites the accompanying narrative, which had leaned on the wrong number. Rolls up the staged v1.1.6–v1.1.12 (the SN-supplement rework: per-test α-budget grid atlas, the diverging blue–white–red under/over color standard, the neutral-hatch Figure 8, and the m0-sourced comparator roster). Deterministic (identical md5 on two runs). Supersedes v1.1.5. v1.1.5 — ✅ 10.5281/zenodo.22260812 (published 2026-09-02) (m02d_fishers_exact_not_exact_reproducibility_v1.1.5.zip, md5 d96e845d54d12ae496fe78d7440ca4c7, 3,413,155 B, 79 files): availability statement consolidated into Declarations; placement made a canonical build check. The data-availability text was appearing twice — as the Availability of data and materials. statement inside Declarations and as a standalone ## Data and code availabilitysection bolted on after the References, which had drifted (the Declarations copy still read placeholder wording while the live DOI lived only in the bolted-on section). Consolidated into the single Declarations statement (scope + no-redistribution; the reproducibility package on Zenodo under the concept DOI as a live link
William Dwyer· Zenodo (CERN European Organi...· 0 citations
Why Fisher's exact test is least exact where it matters most: achieved size, wasted power, and a routing rule for 2×2 tables William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22238930. This release (v1.1.14):10.5281/zenodo.22262453, published Sep 2, 2026; the concept DOI above resolves to it. The previous release, v1.1.13, is 10.5281/zenodo.22262451; earlier, v1.1.5 is 10.5281/zenodo.22260812 and v1.1.4 is 10.5281/zenodo.22260570. What this is The reproducibility deposit for the m02d paper. "Fisher's exact test" is exactly valid — its true rejection rate never exceeds the nominal α — but it is not size-exact: because the 2×2 reference distribution is discrete, no table boundary falls at α, so the achieved (unconditional) size sits below nominal. At small designs the test spends only 26–66% of its α budget, and wasted size is wasted power. The paper computes the achieved size, the wasted-power cost, and the significance-flip behaviour of Fisher's exact against a conservative→liberal roster (Yates χ², Fisher, mid-p, Boschloo, Barnard, Pearson χ², Cressie–Read λ=2/3, likelihood-ratio G), and distills the result into a routing rule for the 2×2. Everything is deterministic exhaustive enumeration — two independent binomials, no Monte Carlo, no random seed — so there is no simulation error: every number, table, and figure reproduces exactly from a named script. The keynote A real-data scan of 6,030 public 2×2 tables (757 pydataset/Rdatasets datasets) shows the tests agree essentially everywhere away from the threshold but disagreement spikes on each decision line — ~67% of tables within ±0.02 of 0.05 and ~76% within ±0.02 of the 0.10 trend line get a test-dependent verdict — so the tests are miscalibrated relative to one another exactly where we use them to draw the significant/not-significant line, and the trend line inherits the same spike. Flips are read on a three-tier taxonomy relative to Boschloo (the valid frontier): conservative below it, valid on it, liberal above it. What the deposit contains Manuscript (author + anonymized, .md), the Derivations companion (D1–D6: conditional validity and the achieved-size shortfall; mid-p as the mean of the median-unbiased rule with E₀[mid-p] = ½; Boschloo's uniform power dominance; the nesting that makes flips one-directional; the atom-lattice gap and exact Boschloo region behind Figure 3; and why conditioning forfeits the budget), the novelty / prior-art companion, and the cover letter(The American Statistician). Reproducibility apparatus (rerun/) — the exact-enumeration engine achieved_size.py (tie-aware conditional p-values, validated against SciPy to 2.2e-16) and the deterministic sweep drivers: power_and_flips.py, size_skew_sweep.py, flip_boundary_sweep.py, roster_sweep.py (the full comparator roster, including the Cressie–Read λ=2/3 power-divergence member), and public_flip_scan.py (the real-corpus scan). Each writes its locked JSON/CSV. Figures (figures/) — the achieved-size and wasted-power panels, the size×skew heat maps, the α=0.05 flip-boundary maps, the χ²-inclusive roster figures, the real-data flip-incidence figure, the routing flowchart (now Figure 9), and the per-test direction butterfly (Figure 8). Interactive demonstrator honest_fisher.html — a self-contained in-browser calculator with the full comparator taxonomy and the live-highlight routing flowchart; its JavaScript engine reproduces the deposited numbers and self-checks a parity badge on load. Deep-dive record (deepdives/) — the supporting analyses, including the size/skew, flip-boundary, χ²-roster, real-data, and computed-clearance write-ups, and the M0u-bundle assessment that reconciles m02d with the author's earlier Monte-Carlo program (below). LICENSE, CITATION.cff, MANIFEST.txt (SHA-256 of every file). The Cressie–Read λ=2/3 reconciliation The roster now carries Cressie–Read λ=2/3, the best-calibrated member of the power-divergence family that also contains Pearson (λ=1) and the G-test (λ=0). Across R×C shapes it is the best-calibrated test in the author's companion Monte-Carlo study; on the pure 2×2 that is m02d's subject, its exact achieved size is 0.062 / 0.053 / 0.055 / 0.055 at the representative designs — still mildly liberal, because small-sample discreteness bites it too. So the paper names λ=2/3 as the calibrated member of the χ² family, scopes the "common χ² defaults overshoot" claim to Pearson/Yates/G, and shows that even the well-chosen asymptotic statistic does not escape the 2×2 discreteness the exact unconditional tests handle — turning a potential referee objection into a strengthening of the routing rule. The companion 18-test Monte-Carlo study independently confirms m02d's Boschloo/Barnard power gap over Fisher (+3 to +10 pp by simulation vs +3.7 to +11.1 pp by exact enumeration here). All computation is deterministic exact enumeration; code is released under the MIT License, and text, figures, and data under CC BY 4.0. The public 2×2 corpus is built from the Rdatasets collection via pydataset; no data are redistributed beyond the illustrative tables cited in the paper. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). Why Fisher's exact test is least exact where it matters most: achieved size, wasted power, and a routing rule for 2×2 tables — reproducibility deposit [Software]. Zenodo.https://doi.org/10.5281/zenodo.22238930 BibTeX: bibtex @software{dwyer_m02d_2026, author = {Dwyer, William J.}, title = {Why Fisher's exact test is least exact where it matters most: achieved size, wasted power, and a routing rule for 2x2 tables --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.22238930}, url = {https://doi.org/10.5281/zenodo.22238930}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in its place. When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.1.14 — ✅ 10.5281/zenodo.22262453 (published 2026-09-02) (m02d_fishers_exact_not_exact_reproducibility_v1.1.14.zip, md5 4977e10c1b632054e3e6609176dde2fd, 3,722,698 B, 94 files): the Boschloo-dominates-Fisher machinery, made explicit. Section 6 now shows the one-line power-dominance mechanism rather than only asserting it: Fisher's own conditional test already has unconditional size ≤ α, so the calibrated Boschloo threshold c satisfies c ≥ α, and because both tests threshold the same statistic the rejection set {Fisher p ≤ α} sits inside {Fisher p ≤ c} table for table — Boschloo rejects wherever Fisher does and more, so it is uniformly at least as powerful, a guarantee that would fail for a differently-ordered unconditional statistic. Derivation D3.4 gains the explicit note that Boschloo and the score-based Barnard test are mutually non-nested (neither uniformly dominates; Barnard's occasional power edge is budget spent, not dominance), and the SN supplement gains a "Why Boschloo, not Barnard, is the valid frontier" note beside the comprehensive roster. Exposition over the existing exact-enumeration output; no computed result, figure, or table changed. Deterministic (identical md5 on two runs). Supersedes v1.1.13. v1.1.13 — ✅ 10.5281/zenodo.22262451 (published 2026-09-02) (m02d_fishers_exact_not_exact_reproducibility_v1.1.13.zip, md5 371a192f5a3ea8ad1e552043a3d68562, 3,721,908 B, 94 files): the comprehensive-roster and full-budget-grid build-out, and the worked-example correction. Adds the sixteen-statistic exact achieved-size-and-power engine comprehensive_roster.py, the full per-test α-budget-grid enginebudget_grid_all.py, the vectorized Boschloo helper boschloo_fast.py (an O(P·K) replacement for the O(n⁴) per-cell sup, verified cell-for-cell against the naive loop, which makes exact enumeration to n = 100 tractable), and the supplement table generator splice_supplement_tables.py. The SN supplement's per-test α-budget grids now run n = 6, 8, …, 20, 25, …, 65, 80, 100 and the big-tent size/power tables use the columns n = 8, 10, 16, 25, 40, 65, 100. Also corrects the worked-example Table S1 Cressie–Read λ = 2/3 value — the deposited 0.1881 ("not significant") was wrong; the exact statistic gives p = 0.0287 (significant), cross-checked against scipy.stats.power_divergence — expands that table to the full sixteen-test roster, and rewrites the accompanying narrative, which had leaned on the wrong number. Rolls up the staged v1.1.6–v1.1.12 (the SN-supplement rework: per-test α-budget grid atlas, the diverging blue–white–red under/over color standard, the neutral-hatch Figure 8, and the m0-sourced comparator roster). Deterministic (identical md5 on two runs). Supersedes v1.1.5. v1.1.5 — ✅ 10.5281/zenodo.22260812 (published 2026-09-02) (m02d_fishers_exact_not_exact_reproducibility_v1.1.5.zip, md5 d96e845d54d12ae496fe78d7440ca4c7, 3,413,155 B, 79 files): availability statement consolidated into Declarations; placement made a canonical build check. The data-availability text was appearing twice — as the Availability of data and materials. statement inside Declarations and as a standalone ## Data and code availabilitysection bolted on after the References, which had drifted (the Declarations copy still read placeholder wording while the live DOI lived only in the bolted-on section). Consolidated into the single Declarations statement (scope + no-redistribution; the reproducibility package on Zenodo under the concept DOI as a live link
William Dwyer· Zenodo (CERN European Organi...· 0 citations
Why Fisher's exact test is not exact: achieved size, wasted power, and a routing rule for 2×2 tables William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22238930. This release (v1.0.5):10.5281/zenodo.22238931. What this is The reproducibility deposit for the m02d paper. "Fisher's exact test" is exactly valid — its true rejection rate never exceeds the nominal α — but it is not size-exact: because the 2×2 reference distribution is discrete, no table boundary falls at α, so the achieved (unconditional) size sits below nominal. At small designs the test spends only 26–66% of its α budget, and wasted size is wasted power. The paper computes the achieved size, the wasted-power cost, and the significance-flip behaviour of Fisher's exact against a conservative→liberal roster (Yates χ², Fisher, mid-p, Boschloo, Barnard, Pearson χ², Cressie–Read λ=2/3, likelihood-ratio G), and distills the result into a routing rule for the 2×2. Everything is deterministic exhaustive enumeration — two independent binomials, no Monte Carlo, no random seed — so there is no simulation error: every number, table, and figure reproduces exactly from a named script. The keynote A real-data scan of 6,030 public 2×2 tables (757 pydataset/Rdatasets datasets) shows the tests agree essentially everywhere away from the threshold but disagree in ~84% of cases inside the Fisher-p band 0.05–0.07 — that is, the tests are miscalibrated relative to one another exactly where we use them to draw the significant/not-significant line. Flips are read on a three-tier taxonomy relative to Boschloo (the valid frontier): conservative below it, valid on it, liberal above it. What the deposit contains Manuscript (author + anonymized, .md), the novelty / prior-art companion, and the cover letter (The American Statistician). Reproducibility apparatus (rerun/) — the exact-enumeration engine achieved_size.py (tie-aware conditional p-values, validated against SciPy to 2.2e-16) and the deterministic sweep drivers: power_and_flips.py, size_skew_sweep.py, flip_boundary_sweep.py, roster_sweep.py (the full comparator roster, including the Cressie–Read λ=2/3 power-divergence member), and public_flip_scan.py (the real-corpus scan). Each writes its locked JSON/CSV. Figures (figures/) — the achieved-size and wasted-power panels, the size×skew heat maps, the α=0.05 flip-boundary maps, the χ²-inclusive roster figures, the real-data flip-incidence figure, and the routing flowchart (Figure 7). Interactive demonstrator honest_fisher.html — a self-contained in-browser calculator with the full comparator taxonomy and the live-highlight routing flowchart; its JavaScript engine reproduces the deposited numbers and self-checks a parity badge on load. Deep-dive record (deepdives/) — the supporting analyses, including the size/skew, flip-boundary, χ²-roster, real-data, and computed-clearance write-ups, and the M0u-bundle assessment that reconciles m02d with the author's earlier Monte-Carlo program (below). LICENSE, CITATION.cff, MANIFEST.txt (SHA-256 of every file). The Cressie–Read λ=2/3 reconciliation The roster now carries Cressie–Read λ=2/3, the best-calibrated member of the power-divergence family that also contains Pearson (λ=1) and the G-test (λ=0). Across R×C shapes it is the best-calibrated test in the author's companion Monte-Carlo study; on the pure 2×2 that is m02d's subject, its exact achieved size is 0.062 / 0.053 / 0.055 / 0.055 at the representative designs — still mildly liberal, because small-sample discreteness bites it too. So the paper names λ=2/3 as the calibrated member of the χ² family, scopes the "common χ² defaults overshoot" claim to Pearson/Yates/G, and shows that even the well-chosen asymptotic statistic does not escape the 2×2 discreteness the exact unconditional tests handle — turning a potential referee objection into a strengthening of the routing rule. The companion 18-test Monte-Carlo study independently confirms m02d's Boschloo/Barnard power gap over Fisher (+3 to +10 pp by simulation vs+3.7 to +11.1 pp by exact enumeration here). All computation is deterministic exact enumeration; code is released under the MIT License, and text, figures, and data under CC BY 4.0. The public 2×2 corpus is built from the Rdatasets collection via pydataset; no data are redistributed beyond the illustrative tables cited in the paper. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). Why Fisher's exact test is not exact: achieved size, wasted power, and a routing rule for 2×2 tables — reproducibility deposit [Software]. Zenodo. https://doi.org/10.5281/zenodo.22238930 BibTeX: bibtex @software{dwyer_m02d_2026, author = {Dwyer, William J.}, title = {Why Fisher's exact test is not exact: achieved size, wasted power, and a routing rule for 2x2 tables --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.22238930}, url = {https://doi.org/10.5281/zenodo.22238930}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in its place. When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.0.6 — staged, not yet uploaded (m02d_fishers_exact_not_exact_reproducibility_v1.0.6.zip, md5 fc3d9dcd5574606e97e5e7f20b434024, 1,848,064 B, 58 files): prior-art citation-completeness pass. Added eight Crossref-verified references — Chen (2011), Neuhäuser & Ruxton (2025), Rudas (1986), Upton (1982), Little (1989), Berger (1996), Routledge (1994), and Hirji (2006) — and, in §8, framed the real-corpus keynote as the empirical, at-scale demonstration of the test-disagreement result Chen (2011) characterized theoretically; §6 now attributes the λ=2/3 calibration to Rudas (1986). No number, figure, table, or claim changed. Upload this version to mint its DOI. v1.0.5 — ✅ 10.5281/zenodo.22238931 (2026-09-01) (m02d_fishers_exact_not_exact_reproducibility_v1.0.5.zip, md5 31f2a7bfeda570ed402dd1aa3fb619e6, 1,846,004 B, 58 files): added the Cressie–Read λ=2/3 member to the roster engine (exact 2×2 achieved size 0.062/0.053/0.055/0.055) and its column to Table 1; scoped the χ²-overshoot claim to the common defaults and named λ=2/3 as the calibrated member (§6); added the Cressie & Read (1984) / Read & Cressie (1988) references and the companion Monte-Carlo self-citation (§9); folded in the M0u-bundle vs m02d assessment deep-dive. Numbers re-verified against the deposited JSON; deterministic (identical md5 on two runs). v1.0.4 — md5 b59f667573823962f999ff040ec591e4, 1,837,352 B, 57 files: routing-flowchart computed-clearance finalizer (Figure 7 and the demonstrator SVG from one audited spec). v1.0.3 — md5 0f01c96e0eb836b2572109446db1b20d, 1,833,339 B: manuscript body expanded to fold the figures/tables with organized in-text callouts; anon regenerated; audits PASS. v1.0.2 — md5 29caf50da2d7bec2409f42098d979e64, 1,830,784 B: full comparator roster and the real-data flip scan added; demonstrator enriched with the taxonomy. v1.0.1 — md5 e0733897cad80d8178d17c8ffcb6943c, 1,714,057 B: size×skew and flip-boundary sweeps + figures. v1.0.0 — md5 54286e0b6841778c71cbea2b20a56897, 1,703,321 B, 48 files: first build — the exact achieved-size engine, the power/flip computation, and the honest_fisher.html demonstrator. Provenance: every number traces to a named, seed-free exact-enumeration script and is validated against SciPy; the demonstrator reproduces the deposited Python. Related work: the companion 18-test Monte-Carlo contingency-table program (M0/M0u), folded into the repo as m0u_work and cited for the Cressie–Read result, the Rényi negative result, and the independent power-gap confirmation.
William Dwyer· Zenodo (CERN European Organi...· 0 citations
An Honest Effect Size for Contingency Tables: Why Nothing Can Be Unbiased, Where to Put the Error Instead, and How to Route the Report William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.21783660. What this is The reproducibility deposit for the point-estimate paper of the contingency-table effect-size arc. The everyday workflow reports Cramér's V and reads it against Cohen's labels; that workflow is biased at the null (Jensen's inequality makes an unbiased estimator of the square-root scale impossible) and treats a noisy point as if it were exact. The paper puts the unavoidable error where it belongs and routes the report: a closed-form O(RC) delete-one jackknife for V² that is nearly unbiased everywhere (at most 0.008 across the 180-design grid, 0.013 as a supremum), a projected confidence interval (conservative but asymptotically valid, any R×C) with an exact-conditional companion for tight coverage, a noise-floor verdict (V_{0.95}) that refuses labels a table cannot support, and a single routing rule that selects the reference (by sparsity and margin heterogeneity), the verdict, the point estimate (by purpose), the scale (always V², negatives permitted and meaningful), and the interval (by whether a guarantee is required). What the deposit contains Manuscript — the built article with the house-standard Key-points box, 8 figures, and 12 numbered/captioned tables (every table carrying an APA bold-label/italic caption and a substantive in-text callout), plus a novelty review companion. Derivations — the compressed derivations ladder and the proof-complete long-form Derivations Companion(Dwyer_M0f_Derivations_Companion_LongForm, ~38 pp, D11–D17 written out in full): the φ² non-U-estimability remark (attributed, with its self-correction), the projected interval as the projection principle instantiated, the affine-link uniqueness, the O(RC) closed-form jackknife, the Bergsma-vs-jackknife crossover equation, and the over-dispersion / two-moment interval fix. Interactive demonstrators — honest_point_estimate.html (the m0f effect-size router: computes the naive V, the jackknifed V², the noise-floor verdict, and the routed report in the browser) and honest_interval.html (the m0g guaranteed-interval sibling), both to the house flip-interpretation standard with a per-cell flip-incidence panel and a seeded null-calibration strip. Reproducibility scripts + locked outputs — every reported number traces to a named, deterministically-seeded script (the bias frontier vs Bergsma's prior, the pooling/meta-analysis collapse, the link/affine-scale test, the projected-interval benchmark, the routing grid, and the figure generators), with the analyzable public-table corpus (effect_size_tables_analyzable.csv) and the routing/flip-incidence scans (rerun/taxonomy_flip_incidence.py, taxonomy_grid_sim.py, and the m0g interval scans) included so the embedded numbers are traceable from the deposit. Real-data evidence — across 4,129 public contingency tables the label-vs-noise-floor recalibration runs both ways (615 forward / 450 reverse); the guaranteed-interval sibling withdraws a claimed resolution on 312 of 2,391 tables (13%, near-pure one-directional deflation). Figures and the deterministic deposit build (fixed timestamps → stable md5; a SHA-256 MANIFEST.txt listing every file). All evaluation is simulation-based; the one empirical component is the public-table scan, which uses only openly distributed data. Code is released under the MIT License; text and figures under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). An Honest Effect Size for Contingency Tables: Why Nothing Can Be Unbiased, Where to Put the Error Instead, and How to Route the Report — reproducibility deposit [Software]. Zenodo.https://doi.org/10.5281/zenodo.21783660 BibTeX: bibtex @software{dwyer_m0f_2026, author = {Dwyer, William J.}, title = {An Honest Effect Size for Contingency Tables: Why Nothing Can Be Unbiased, Where to Put the Error Instead, and How to Route the Report --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.21783660}, url = {https://doi.org/10.5281/zenodo.21783660}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release, use that version's DOI and add version = {v1.2.NN}. When the accompanying journal article is published, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history (consolidated changelog) Published version DOIs are marked ✅; the concept DOI above always resolves to the latest. Staged versions were rolled into the next published one unless noted. v1.2.11 ⏳ (staged 2026-09-01) — Live availability-DOI link + deepened table callouts (documents-only; no result, number, figure, or datum changed). The manuscript's Availability of data and materials statement now renders the concept DOI as a functional, clickable hyperlink in the built docx/pdf (was literal [...](...) text) — the m0-family docx builder was taught to render markdown [text](url) as a real hyperlink, resolving the reason the Behavior Research Methods editorial office returned the submission. The Table 11 and Table 12 callouts were deepened to point the reader at specific rows/values (float_callout substantive 0.35 → 0.45). Manuscript docx/pdf rebuilt from unchanged source; MANIFEST regenerated. v1.2.10 ✅ 10.5281/zenodo.22151244 (2026-08-28) — Long-form Derivations Companion added (~38 pp, D11–D17 written out in full) alongside the compressed ladder; documents-only, structure + math-render audits pass. v1.2.9 ✅ 10.5281/zenodo.22139670 (2026-08-28) — Routing-domain validation. Both browser demonstrators resolve flip incidence across the routing taxonomy (m0f: 615 forward / 450 reverse label-vs-floor recalibrations over 4,129 public tables; m0g: 312 of 2,391 guaranteed-interval withdrawals), with new reproducible scans, deposited JSON/CSV outputs, the analyzable public-table corpus, and two taxonomy deep-dives. v1.2.8 (2026-08-28) — De-bolded for verbal emphasis; Key-points highlights; refreshed novelty review.Emphasis-bold minimized (170 → ~42 spans; all 744 numeric tokens verified byte-identical), a house-standard seven-bullet Key-points box added after the abstract, and the novelty review rewritten to the clean strand-by-strand form. Presentation only; rolled into v1.2.9. v1.2.7 (2026-08-28) — Tables numbered, captioned, and called out. All 12 tables numbered (Table 1–12), given APA bold-label/italic captions, and referenced in the body (float_callout depth 1.00). Organization only; rolled into v1.2.9. v1.2.6 ✅ 10.5281/zenodo.22135868 (2026-08-27) — Routing-flowchart polish. Consistent ①–⑤ stage numbering (the scale stage is now a numbered pass-through in the figure too), vertical centering of decision-box titles, STOP-box clearance, rounded modal corners, and a legible star default marker. Presentation only. v1.2.1–v1.2.5 (2026-08-27) — The routing flowchart brought to a single house edge-label spec (figure + pop-up generated from one source), box-sizing / no-touching-boxes overlap guard, the pop-up flowchart aligned to the manuscript figure's visual style, and the browser tool taken to the flip-interpretation standard. Presentation + tooling; no result changed; rolled into v1.2.6. v1.2.0 ✅ 10.5281/zenodo.22003886 (2026-08-18) — Over-dispersion interval. The over-dispersion mechanism for the noncentral-interval drift and the derived two-moment ρ-interval (ρ_ci tight + ρ_ci_guard conservative, any R×C, JS-ported), rewriting Section 6.3 + Figure 6 and derivation D17 and superseding the earlier endpoint patch. v1.1.1 ✅ 10.5281/zenodo.21784544 (2026-08-04) — Earlier public release of the point-estimate package. Provenance: every number traces to a named, deterministically-seeded script listed in the manuscript Declarations; the two browser demonstrators reproduce the deposited Python, and the deposit build is deterministic (fixed timestamps → stable md5, SHA-256 MANIFEST).
William Dwyer· Zenodo (CERN European Organi...· 11 citations
The trace-gamma distribution: a three-cumulant calibrated reference for quadratic-form tests, with Welch's F and Pearson's χ² as special cases William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22060095. Published v1.0.13:10.5281/zenodo.22143061. What this is The reproducibility deposit for the trace-gamma paper. Many everyday tests are quadratic forms in approximately-normal estimates — Welch's heteroscedastic F, Pearson's χ² of independence, score and Wald statistics — and their exact null is a generalized chi-square (a weighted mix of χ²'s) that software almost always replaces with a one- or two-moment approximation. Those approximations miscalibrate exactly where it matters: few groups, unequal variances, sparse or skewed data. The paper introduces the trace-gamma distribution, a three-cumulant calibrated reference built from the quadratic form's own mean, variance, and third cumulant via the Lancaster cumulant-trace identity, and shows that Welch's F and Pearson's χ² fall out as special cases. It matches the exact Imhof (1961) inversion across a wide design grid, carries an estimable non-Gaussian cumulant correction, and — deployed as a test reference — is a deflation of the naive two-moment call (its rejection region is a strict subset, so a significant result can only be withdrawn, never manufactured; no reverse flip is possible). What the deposit contains Manuscript (author + anonymized; built .docx/.pdf), the novelty / prior-art companion, and the long-form derivations companion (D1–D8, proof-complete: the generalized-chi-square null, the Lancaster cumulant-trace identity, the trace-gamma parameterization, and the arguments behind Propositions 1–6). Reproducibility apparatus — the distribution object mseries_qgamma.py (TraceGamma, constructors from cumulants), the four cross-checks validate_qgamma.py, the base experiments qgamma_experiments.py (V1–V3), the estimable cumulant correction, the exact Imhof-inversion cross-check qgamma_imhof.py, the wider design grid (group size × imbalance × input shape), and the deployed stress grid — each with its locked CSV. Every reported number regenerates from these deterministically-seeded scripts. Figures — the accuracy panels, the cumulant-correction figure, the design-grid and stress-grid figures, and the Imhof cross-check. Interactive demonstrator honest_tracegamma.html — computes the two-cumulant-vs-trace-gamma verdict flip and its population incidence in the browser, reproduces the deposited Python, and carries the house flip-interpretation standard (deflation marker, "how to read a flip" beat, incidence panel, assertNoReverse). Deep-dive record and the submission apparatus. All evaluation is simulation-based with an exact-inversion cross-check. Code is released under the MIT License; text, figures, and data under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). The trace-gamma distribution: a three-cumulant calibrated reference for quadratic-form tests — reproducibility deposit [Software]. Zenodo. https://doi.org/10.5281/zenodo.22060095 BibTeX: bibtex @software{dwyer_tracegamma_2026, author = {Dwyer, William J.}, title = {The trace-gamma distribution: a three-cumulant calibrated reference for quadratic-form tests --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.22060095}, url = {https://doi.org/10.5281/zenodo.22060095}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in place of it (e.g. 10.5281/zenodo.22143061 for v1.0.13). When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.0.14 — ✅ 10.5281/zenodo.22187379 (2026-08-31) staged (pending upload): rendering-only refresh — the manuscript and Derivations Companion docx/PDF rebuilt through the current math-typography builder so nested-paren radicals draw as true Office-math radicals; the deposit now also carries the current shared house tooling (the bundled mseries_deposit.py includes the require_all deposit guard). No number, figure, table, or claim changed; the 71 in-text cross-reference links are intact. New version on concept 10.5281/zenodo.22060095 (tracegamma_reproducibility_v1.0.14.zip, md5 6f6a0e5c1e29d6cd3fa34008458666f0, 9,937,855 B, 59 files). v1.0.13 — ✅ 10.5281/zenodo.22143061 (2026-08-28). v1.0.12 — ✅ 10.5281/zenodo.22142142 (2026-08-28): two companion documents added — the novelty/prior-art review and the full-detail D1–D8 derivations ladder; §6 now points to the derivations companion; body unchanged. v1.0.11 — ✅ 10.5281/zenodo.22132594 (2026-08-27): cover letter brought to the house standard; first fully deterministic (byte-reproducible) deposit. v1.0.10 — ✅ 10.5281/zenodo.22125099 (2026-08-27): restored the in-text cross-reference hyperlinks in the Word/PDF. v1.0.0 — first deposit (10.5281/zenodo.22060096; concept 10.5281/zenodo.22060095): the trace-gamma distribution object, the Imhof cross-check, the design grid, and the honest_tracegamma.html demonstrator. Provenance: every number traces to a named, deterministically-seeded script and is cross-checked against the exact Imhof (1961) inversion; the demonstrator reproduces the deposited Python. Related records: the T_root methodology 10.5281/zenodo.21522471; the ANOVA sibling m01A 10.5281/zenodo.21908169.
William Dwyer· Zenodo (CERN European Organi...· 0 citations
A guaranteed-level repair for Welch's two-sample t, which silently over-rejects under skew, heteroscedasticity, and small samples William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22036361. Published v1.4.3:10.5281/zenodo.22104110. What this is The reproducibility deposit for the m01t paper — the two-sample companion to the guaranteed-level ANOVA work (m01A/m01x). Welch's two-sample t is the field default for comparing two means under unequal variances, but at the corner where the data are skewed and heteroscedastic and the samples are small it runs liberal: it rejects the null more often than its nominal level allows. A scan of 515 real public-data comparisons finds that about one in three borderline-significant Welch results do not survive a level-guaranteed test — a concrete, real-data measure of the over-rejection. m01t specializes the companion procedure's Berger-Boos deflation to two groups: it deflates the known-variance quadratic by a closed-form radius built from each group's kurtosis-widened variance instability and refers the result to a chi-square. The test holds worst-case size at or below nominal exactly where Welch is liberal; its raw conservatism is the honest cost of the guarantee, and size-adjusted it matches Welch to within about 0.02 in power. The deposit ships the browser demonstrator honest_ttest.html, which computes Welch beside the guaranteed T_BB on your own data and prints the honest receipt — a deflation mechanism (the guaranteed rejection region is a strict subset of Welch's, so a significant call can only ever be withdrawn, never manufactured; no reverse flip is possible). What the deposit contains Manuscript (author + anonymized; built .docx/.pdf), the novelty / prior-art companion, and the derivationscompanion (the two-group Berger-Boos radius, the kurtosis-widening bound, the size proof, and the one-sided variant). Reproducibility apparatus — the simulation runners (the shared-grid scoreboard, the Fleishman skew×kurtosis decomposition grid, the competitor and gate-ablation runners) and the locked result CSVs. Every reported number regenerates from these deterministically-seeded scripts. Figures — the headline, the Welch over-rejection heat map, the validity-versus-power frontier, the method × stress-regime worst-size heat map, the per-method failure map, the kurtosis-axis curve, and the orthogonal-axis decomposition of Welch's realized size. Interactive demonstrator honest_ttest.html — reproduces the deposited Python exactly and carries the house flip-interpretation standard (deflation marker, "how to read a flip" beat, real-data incidence panel, and an assertNoReverseload guard). Deep-dive record (transfer/power-comparison, the 12-cell flip taxonomy with citations, the declarations and reference-block fixes, the decomposition study) and the submission apparatus. All evaluation is simulation-based. Code is released under the MIT License; text, figures, and data under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). A guaranteed-level repair for Welch's two-sample t — reproducibility deposit[Software]. Zenodo. https://doi.org/10.5281/zenodo.22036361 BibTeX: bibtex @software{dwyer_m01t_2026, author = {Dwyer, William J.}, title = {A guaranteed-level repair for Welch's two-sample t --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.22036361}, url = {https://doi.org/10.5281/zenodo.22036361}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in place of it (e.g. 10.5281/zenodo.22104110 for v1.4.3). When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.4.4 — ✅ 10.5281/zenodo.22187004 (2026-08-31) staged (pending upload): rendering-only refresh — the manuscript and Derivations docx/PDF rebuilt through the current math-typography builder so nested-paren radicals draw as true Office-math radicals; the deposit now also carries the current shared house tooling (the bundled mseries_deposit.py includes the require_all deposit guard). No number, figure, table, or claim changed. New version on concept 10.5281/zenodo.22036361 (m01t_reproducibility_v1.4.4.zip, md5 6e4e09e7dd1a5a747fa1493db94c922d, 3,561,269 B, 73 files). v1.4.3 — ✅ 10.5281/zenodo.22104110 (2026-08-24): arXiv source refreshed; declarations split into separate paragraphs; reference-block one-per-line fix. v1.4.2 — ✅ 10.5281/zenodo.22103410 · v1.4.1 — ✅ 10.5281/zenodo.22102558 · v1.4.0 (2026-08-23): new Figure 8, the orthogonal skew/kurtosis decomposition of Welch's realized size (Fleishman power method; kurtosis alone does not inflate the two-sided size, T_BB holds throughout). v1.3.0 — ✅ 10.5281/zenodo.22054950 (2026-08-22): deposit-scale shared-grid contest fold (40,000 reps, B=699); Table 6 becomes a five-method property scorecard; four contest figures added. v1.1.0 — ✅ 10.5281/zenodo.22036735 (2026-08-21): reviewer- hardening leads folded (held-out-family validity, Monte-Carlo CI on the worst-case size, studentized bootstrap-t and permutation benchmarks, the one-sided T_BB). v1.0.0 — first deposit (concept 10.5281/zenodo.22036361): the guaranteed-level two-group repair, the 515-comparison public-data flip scan, and the honest_ttest.html demonstrator. Provenance: every number traces to a named, deterministically-seeded runner; the demonstrator reproduces the deposited Python (parity self-checked on load). Related records: the one-way ANOVA sibling m01A 10.5281/zenodo.21908169; the moderated-Welch record m01x; the T_root methodology 10.5281/zenodo.21522471.
William Dwyer· Zenodo (CERN European Organi...· 0 citations
The deflated-Welch statistic: a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.21908169. What this is The reproducibility deposit for the deflated-Welch statistic T_BB, a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA (the Behrens–Fisher problem for k ≥ 3 groups). Welch's test becomes liberal under skew and unstable variance weights at small samples; T_BB = Q(s²)·exp(−R) keeps the ordinary group means and buys a guaranteed level by deflating the Welch quadratic by a Berger–Boos scale-inflation radius R. Three operating points are provided: a fixedcalibrated radius (κ_s), a design-adaptive near-guarantee radius (closed-form polygamma Cornish–Fisher with a finite-nkurtosis guard), and a fully proved smallest-eigenvalue radius R_eig (Gaussian, extended under bounded kurtosis). What the deposit contains Manuscript (author + anonymized) and a derivations supplement (DA1–DA13) plus a long-form derivations companion, covering: why Welch fails under skew in closed form; the Berger–Boos deflation and its exact worst-case radius; the polygamma-cumulant Cornish–Fisher radius with saddlepoint-exact normal backbone; the excess-kurtosis tail term with its finite-n upper-confidence guard; the imbalance correction; the fully proved smallest-eigenvalue radius (with the k-group multiplicity fix, free-β optimization, and the proved-under-bounded-kurtosis widening); and the k-sample Behrens–Fisher null distribution. Interactive demonstrator rerun_cochran/honest_anova.html — computes raw-mean Welch, the fixed / adaptive / proved T_BB radii, the estimand-changing transform routes, and the full routing receipt in the browser, reproducing the deposited Python. Its engine is extracted as a standalone Node module (m01A_anova_engine.js) and checked cell-by-cell against Python across an 84-design taxonomy (verify_anova_engine_taxonomy.py/.js, max |Δp| = 0.00000). Reproducibility scripts (rerun_cochran/, rerun/) — every reported number traces to a named, deterministically-seeded script (size/power/surface, the calibration and information-limit decompositions, the proved-radius verification, the imbalance calibration, the skew-router branch, and the figures). Real-data evidence — anova_flip_scan.py scans 2,783 public one-way layouts (254 datasets): guaranteed T_BBwithholds ~41% of Welch-significant calls, concentrated where the weight-instability screen fires, and never manufactures significance (Table 7 / Figure 15). Figures and the deterministic deposit builder (fixed timestamps → stable md5). All evaluation is simulation-based; the one empirical component is the public-dataset scan, which uses only openly distributed data. Code is released under the MIT License; text and figures under CC BY 4.0. Version history (consolidated changelog) Published version DOIs are marked ✅; the concept DOI above always resolves to the latest. Staged versions were rolled into the next published one unless noted. v1.0.77 ✅ 10.5281/zenodo.22167690 (2026-08-30): CSDA guide-for-authors conformance — abstract trimmed to 247 words (from 284), keywords cut to 7 (from 11), the withholding highlight shortened to ≤85 characters, and the arXiv PDF/source regenerated. No change to methods, results, figures, or code. v1.0.76 ✅ 10.5281/zenodo.22167536 (2026-08-30) — AI-disclosure heading aligned to Elsevier. The manuscript's declaration heading is now "Declaration of generative AI and AI-assisted technologies in the manuscript preparation process" (was "Use of generative AI"); the disclosure body is unchanged. Prepared alongside an Elsevier-compliant cover-letter variant and an EM suggested-reviewer sheet (both kept outside the deposit). docx/pdf rebuilt; deterministic md5 refreshed. v1.0.75 ✅ 10.5281/zenodo.22167304 (2026-08-30) — Submission-sharpening pass. Graphical abstract + Elsevier Highlights; figures and tables renumbered into reading order with per-table Source clauses; the validity–power frontier (Figure 8) now carries the proved R_eig operating point (100% validity, size-adjusted power 0.613, merge_tbb_proved_frontier.py); new Section 7 "Recovering power by design" + Table 8 (rc_anova_power_by_design.py); and a live required-n calculator in honest_anova.html (per-group and total n for 80% power, "power now @ total n"), with a numeric-heading CSS fix and the engine re-verified against Python at 0.00000. v1.0.74 ✅ 10.5281/zenodo.22165892 (2026-08-29) — Proved-under-bounded-kurtosis radius (DA12.6). The proved non-normal widening now keys on excess kurtosis, √(1 + κ̂·(n−1)/(2n)), from the exact Var(s²/σ²) = 2/(n−1) + κ/n, so symmetric heavy tails (Student-t) are covered where the old skew form √(1 + 0.75·skew²) under-covered; tbbProvedswitched to the kurtosis form across the demonstrator, engine, and Python truth (re-verified JS-vs-Python at 0.00000); new rc_anova_kurtosis_proof.py + deep-dive. v1.0.73 ✅ 10.5281/zenodo.22165709 (2026-08-29) — Reconstructed & verified demonstrator engine (standalone Node module + taxonomy verifier, max |Δp| = 0.00000 across 84 designs; Yuen zero-variance fix; T_BB-routed presets both directions); series-impact deep-dive (the corrected R_eig k-group multiplicity gap also reaches m03 and m01t). v1.0.72 (2026-08-29) — Title set to "The deflated-Welch statistic…"; corrected + optimized proved radius R_eig (β/k multiplicity fix + β-optimization, DA12); real-data Welch-vs-T_BB flip scan (2,783 layouts; Table 7 / Figure 15) + demonstrator imbalance-factor fix; long-form derivations companion. v1.0.71 / v1.0.70 (2026-08-21) — Zhang normal-reference comparator benchmarked on the efficiency frontier (valid on only 24% of designs, in the calibrated-liberal cluster); k = 2 adaptive-radius case-study fold (design-scaling vs shape-keying distinction). v1.0.69 ✅ 10.5281/zenodo.22035826 (2026-08-20) — HTML R1/R2 presentation pass + Figure 9 adaptive per-cluster label merge. v1.0.68 ✅ 10.5281/zenodo.22033737 (2026-08-20) — Companion consolidation into a single six-column Table 6; Figures 11–14 harmonized into one story. v1.0.67 / v1.0.65 / v1.0.60 (2026-08-19/20) — Guarded-reference naming-collision fix; the 40,000-replication expanded-frontier pin (Table 3 + Figure 8) with the symmetric-heteroscedastic skew-router branch; the mean-preserving lightened-R_eig do-not-use fallback. v1.0.59 ✅ 10.5281/zenodo.21995320 (2026-08-18) — Reporting standard + honest_anova.html demonstrator re-aligned to the current T_BB methods paper. v1.0.57 ✅ 10.5281/zenodo.21986847 (2026-08-17) — Reviewer-comprehension pass (multi-paragraph abstract, contributions list, trimmed captions); proved radius R_eig added as a Table 3 scorecard row; corner tail-index correction (N−k)/2 (low-order moments exist in every deployed design). v1.0.56–v1.0.49 (2026-08-16) — The k-sample Behrens–Fisher corner-distribution program: two-moment scaled-χ² corner reference, derived corner cumulants, the secular-eigenvalue law + closed CGF + power-law tail, consolidated into derivations DA13 with a prior-art/novelty audit. v1.0.48 ✅ 10.5281/zenodo.21963458 (2026-08-16) — The unifying λ(z) correction (a smooth instability-keyed deflation strength). v1.0.45 ✅ 10.5281/zenodo.21962965 (2026-08-16) — Atomic sparsity index + bootstrap-t edge hardening + shape-aware pooled standardized-residual bootstrap (SA-PSRB); multivariate transfer to m03. v1.0.44–v1.0.41 (2026-08-16) — Shape-moment re-injection order (skew is the sweet spot), validated and hardened pooled standardized-residual bootstrap, atomic weight-noise probes. v1.0.40 ✅ 10.5281/zenodo.21961667 (2026-08-16) — Log-domain weight-stabilization probe (negative for stabilization; clarifies the size-adjusted oracle ceiling); includes the oracle-power gap decomposition (≈92% conservatism, ≈8% estimation). v1.0.37 ✅ 10.5281/zenodo.21961327 (2026-08-16) — Residual-bootstrap qualification of the shoot-out + the first proved Gaussian smallest-eigenvalue radius R_eig (DA12, the p = 1 specialization of the m03 theorem). v1.0.36 (2026-08-15) — Figure 11 T_BB-region colour fix (amber, matching the routing figures). v1.0.27 ✅ 10.5281/zenodo.21908170 — Earlier published baseline of the deposit. Provenance: every number traces to a named, deterministically-seeded script listed in the manuscript Declarations; the demonstrator engine reproduces the deposited Python to max |Δp| = 0.00000 across the taxonomy verification. License. Code and scripts in the deposit are released under the MIT License; text and figures under CC BY 4.0. Reuse is permitted with attribution to the author and citation of the concept DOI above. How to cite. Dwyer, W. J. The deflated-Welch statistic: a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA. Reproducibility deposit, Zenodo. https://doi.org/10.5281/zenodo.21908169
William Dwyer· Zenodo (CERN European Organi...· 3 citations
Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.21844797. Published v1.0.0:10.5281/zenodo.21844798. What this is The reproducibility deposit for a single combined manuscript on detecting sparse departures from independence in a two-way contingency table — the regime where dependence hides in a few cells rather than spreading across the table, so the omnibus chi-square is under-powered and a naive per-cell scan mis-calibrates. It is organized in three parts under one set of front/back matter, with a shared derivations supplement (D02): Part I — the heteroscedasticity profile and the detection boundary. The per-cell standardized deviations are heteroscedastic under the margin-conditional null; profiling that heteroscedasticity gives a closed-form detection boundary separating the sparsity/strength regimes where any test can succeed from those where none can. Part II — an adaptive higher-criticism gate. A higher-criticism statistic tuned to the margin-conditional cell law attains that boundary, with its exact null law and power characterized. Part III — an assumption-lean exact anchor and reporting apparatus. An exact margin-conditional calibration anchor and a routing rule, so a scan that mis-sizes under the asymptotic reference is replaced by one that holds its level: on a corpus of 5,543 real tables the asymptotic per-cell scan mis-sizes about two-thirds of them (mean realized size ≈ 0.33 against a 0.05 target) while the exact anchor holds near 0.01. What the deposit contains Combined manuscript (manuscripts/Dwyer_M02_Combined.{docx,pdf} + M02_Combined_Manuscript.md) and the three part-sources (manuscripts/parts/, provenance for the assembled combined text), plus the D02 derivations companion (derivations/). Verification and study code (code/) — the boundary, exact-anchor, and higher-criticism verification scripts and the power/size study drivers (numpy/scipy, fixed seeds); the docx builder (build_docx.py), the shared math-typography core (mseries_mathtype.py), the inline- and caption-math delimiters, the combined assembler (assemble_combined.py), and the audit gates (structure_audit.py, math_render_audit.py). Locked data (data/) — the study outputs (size/power, boundary, estimated-margins, efficiency) and the higher-replication "big box" runs, so every number regenerates. Figures (figures/), the novelty reviews (novelty_reviews/), the prior-art / adversarial / consistency audits (audits/), and the in-browser detector tools/honest_detection.html. All evaluation is simulation-based; the one empirical component is the public-corpus calibration scan, which uses only openly distributed contingency tables. Code is released under the MIT License; text, figures, and data under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor — reproducibility deposit [Software]. Zenodo. https://doi.org/10.5281/zenodo.21844797 BibTeX: bibtex @software{dwyer_m02_2026, author = {Dwyer, William J.}, title = {Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.21844797}, url = {https://doi.org/10.5281/zenodo.21844797}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in place of it (e.g. 10.5281/zenodo.21844798 for v1.0.0). When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.0.3 — deterministic recut (2026-08-30): the bundle is now cut with the shared mseries_deposit.write_deterministic_zip, so rebuilding the same content yields a byte-identical zip and a stable md5. Every manuscript, derivation, figure, dataset, code file, novelty review, and audit is byte-identical to v1.0.2 (all files SHA-256-matched except the three version-stamped ones). No number, theorem, table, figure, or dataset changed. Publishes as a New Version on concept 10.5281/zenodo.21844797 (build_m02_deposit.py; md5 8f2fa9f7e814ba807710480a7f60cb65, 112 files, 6,044,685 bytes). v1.0.2 — impact-first reframe (2026-08-23): the introduction and abstract reframed to lead with the applied motivation (sparse independence departures in genomics, network/text co-occurrence, pharmacovigilance, ecology, survey cross-tabulation) and the corpus calibration failure, before the detection-boundary theory. No number, theorem, figure, or dataset changed. v1.0.1 — published (2026-08-08): adds the Zenodo concept DOI to the manuscript Availability statement and CITATION.cff, and the widened Figure 8 top box. Content otherwise identical to v1.0.0. v1.0.0 ✅ 10.5281/zenodo.21844798 — first published deposit: the combined three-part manuscript, the D02 derivations, the verification and study code with fixed seeds and locked outputs, all figures, the in-browser detector, and the prior-art / adversarial / consistency audits. Provenance: every number traces to a named, deterministically-seeded script under code/; the combined manuscript is assembled by code/assemble_combined.py and built by code/build_docx.py. Related identifiers: T_root methodology 10.5281/zenodo.21522471; exact conditional engine 10.5281/zenodo.21831680.
William Dwyer· Zenodo (CERN European Organi...· 0 citations
A guaranteed-coverage confidence interval for the two-sample standardized effect William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): minted on first publication. What this is The reproducibility deposit for the m01te methods paper: a guaranteed-coverage confidence interval for the two-sample standardized effect (Cohen's d) at the skewed, unequal-variance, small-n corner where the textbook interval silently under-covers. The noncentral-t inversion assumes normal data and equal variances; at a lognormal, four-to-one variance-ratio, n = 10 design its realized coverage falls to 0.81 against a nominal 0.95, and a naive percentile bootstrap of dfalls further, to 0.78 — a joint failure of the mean-difference reference and the variance estimate that standardizes it, which resampling does not repair. The paper gives a three-tier recommendation, mirroring the companion two-sample test and the one-way effect-size paper: Classical — the noncentral-t / normal-approximation interval, the everyday default, liberal at the corner. Calibrated middle tier — the guaranteed two-sample test T_BB inverted for the mean difference at the full level, divided by the plug-in pooled scale. Closed-form and deterministic (no resampling), with near-nominal worst-case coverage 0.93 at about 1.6× the classical width. It keeps the mean-difference deflation that repairs the actual under-coverage while treating the scale at its point estimate; the over-covering numerator and the under-covering plugged-in scale roughly cancel to near nominal. Guaranteed floor — a Bonferroni combination of the T_BB-inverted mean-difference interval with a distribution-free bootstrap scale interval, carrying a proved finite-sample coverage floor (worst-case 0.97) at about 4× the classical width. What the deposit contains Manuscript (author + anonymized markdown; built .docx/.pdf, including a cross-reference–hyperlinked variant) and the derivations (D1–D6): the estimand and its d_av scale; the T_BB-inverted mean-difference interval; the exact Bonferroni coverage floor of the ratio interval; why the classical standard error under-covers off its normal/equal-variance premise; the deterministic-simulation confirmation; and the calibrated middle tier with its compensation argument. Reproducibility runner — rerun/rc_m01te_coverage.py computes, for each design cell across the parent-distribution × sample-size × variance-ratio × effect grid, the realized coverage and mean width of all four intervals (classical, percentile-bootstrap, calibrated middle, guaranteed floor). Every number regenerates from this deterministically-seeded script (seed 20260826); its locked output CSV is deposited. Figure — figures/m01te_coverage.png (built by make_m01te_figure.py): the four coverage curves cell by cell across the grid, the classical and bootstrap curves sliding below nominal at the corner, the calibrated curve tracking near it, and the guaranteed curve holding above it. All evaluation is simulation-based. Code is released under the MIT License; text and figures under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). A guaranteed-coverage confidence interval for the two-sample standardized effect: reproducibility deposit (Version 1.0.0) [Software]. Zenodo. https://doi.org/⟨concept DOI⟩
William Dwyer· Zenodo (CERN European Organi...· 0 citations
A guaranteed-coverage confidence interval for the two-sample standardized effect William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22114522. Published v1.0.0:10.5281/zenodo.22114523 (2026-08-26, the earlier two-tier construction). The three-tier update described below is staged as a pending new version (v1.1.0) on the same concept DOI. What this is The reproducibility deposit for the m01te methods paper: a guaranteed-coverage confidence interval for the two-sample standardized effect (Cohen's d) at the skewed, unequal-variance, small-n corner where the textbook interval silently under-covers. The noncentral-t inversion assumes normal data and equal variances; at a lognormal, four-to-one variance-ratio, n = 10 design its realized coverage falls to 0.81 against a nominal 0.95, and a naive percentile bootstrap of dfalls further, to 0.78 — a joint failure of the mean-difference reference and the variance estimate that standardizes it, which resampling does not repair. The paper gives a three-tier recommendation, mirroring the companion two-sample test and the one-way effect-size paper: Classical — the noncentral-t / normal-approximation interval, the everyday default, liberal at the corner. Calibrated middle tier — the guaranteed two-sample test T_BB inverted for the mean difference at the full level, divided by the plug-in pooled scale. Closed-form and deterministic (no resampling), with near-nominal worst-case coverage 0.93 at about 1.6× the classical width. It keeps the mean-difference deflation that repairs the actual under-coverage while treating the scale at its point estimate; the over-covering numerator and the under-covering plugged-in scale roughly cancel to near nominal. Guaranteed floor — a Bonferroni combination of the T_BB-inverted mean-difference interval with a distribution-free bootstrap scale interval, carrying a proved finite-sample coverage floor (worst-case 0.97) at about 4× the classical width. What the deposit contains Manuscript (author + anonymized markdown; built .docx/.pdf, including a cross-reference–hyperlinked variant) and the derivations (D1–D6): the estimand and its d_av scale; the T_BB-inverted mean-difference interval; the exact Bonferroni coverage floor of the ratio interval; why the classical standard error under-covers off its normal/equal-variance premise; the deterministic-simulation confirmation; and the calibrated middle tier with its compensation argument. Reproducibility runner — rerun/rc_m01te_coverage.py computes, for each design cell across the parent-distribution × sample-size × variance-ratio × effect grid, the realized coverage and mean width of all four intervals (classical, percentile-bootstrap, calibrated middle, guaranteed floor). Every number regenerates from this deterministically-seeded script (seed 20260826); its locked output CSV is deposited. Figure — figures/m01te_coverage.png (built by make_m01te_figure.py): the four coverage curves cell by cell across the grid, the classical and bootstrap curves sliding below nominal at the corner, the calibrated curve tracking near it, and the guaranteed curve holding above it. All evaluation is simulation-based. Code is released under the MIT License; text and figures under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). A guaranteed-coverage confidence interval for the two-sample standardized effect: reproducibility deposit (Version 1.0.0) [Software]. Zenodo. https://doi.org/10.5281/zenodo.22114522
William Dwyer· Zenodo (CERN European Organi...· 0 citations
Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.21844797. Published v1.0.0:10.5281/zenodo.21844798. What this is The reproducibility deposit for a single combined manuscript on detecting sparse departures from independence in a two-way contingency table — the regime where dependence hides in a few cells rather than spreading across the table, so the omnibus chi-square is under-powered and a naive per-cell scan mis-calibrates. It is organized in three parts under one set of front/back matter, with a shared derivations supplement (D02): Part I — the heteroscedasticity profile and the detection boundary. The per-cell standardized deviations are heteroscedastic under the margin-conditional null; profiling that heteroscedasticity gives a closed-form detection boundary separating the sparsity/strength regimes where any test can succeed from those where none can. Part II — an adaptive higher-criticism gate. A higher-criticism statistic tuned to the margin-conditional cell law attains that boundary, with its exact null law and power characterized. Part III — an assumption-lean exact anchor and reporting apparatus. An exact margin-conditional calibration anchor and a routing rule, so a scan that mis-sizes under the asymptotic reference is replaced by one that holds its level: on a corpus of 5,543 real tables the asymptotic per-cell scan mis-sizes about two-thirds of them (mean realized size ≈ 0.33 against a 0.05 target) while the exact anchor holds near 0.01. What the deposit contains Combined manuscript (manuscripts/Dwyer_M02_Combined.{docx,pdf} + M02_Combined_Manuscript.md) and the three part-sources (manuscripts/parts/, provenance for the assembled combined text), plus the D02 derivations companion (derivations/). Verification and study code (code/) — the boundary, exact-anchor, and higher-criticism verification scripts and the power/size study drivers (numpy/scipy, fixed seeds); the docx builder (build_docx.py), the shared math-typography core (mseries_mathtype.py), the inline- and caption-math delimiters, the combined assembler (assemble_combined.py), and the audit gates (structure_audit.py, math_render_audit.py). Locked data (data/) — the study outputs (size/power, boundary, estimated-margins, efficiency) and the higher-replication "big box" runs, so every number regenerates. Figures (figures/), the novelty reviews (novelty_reviews/), the prior-art / adversarial / consistency audits (audits/), and the in-browser detector tools/honest_detection.html. All evaluation is simulation-based; the one empirical component is the public-corpus calibration scan, which uses only openly distributed contingency tables. Code is released under the MIT License; text, figures, and data under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor — reproducibility deposit [Software]. Zenodo. https://doi.org/10.5281/zenodo.21844797 BibTeX: bibtex @software{dwyer_m02_2026, author = {Dwyer, William J.}, title = {Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor --- reproducibility deposit}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.21844797}, url = {https://doi.org/10.5281/zenodo.21844797}, orcid = {0009-0004-0855-7222} } The DOI above is the concept DOI (resolves to the latest version); to cite a specific release use that version's DOI in place of it (e.g. 10.5281/zenodo.21844798 for v1.0.0). When the accompanying journal article appears, please cite it as the primary reference for the method and this deposit as the reproducibility archive. Version history v1.0.3 — deterministic recut (2026-08-30): the bundle is now cut with the shared mseries_deposit.write_deterministic_zip, so rebuilding the same content yields a byte-identical zip and a stable md5. Every manuscript, derivation, figure, dataset, code file, novelty review, and audit is byte-identical to v1.0.2 (all files SHA-256-matched except the three version-stamped ones). No number, theorem, table, figure, or dataset changed. Publishes as a New Version on concept 10.5281/zenodo.21844797 (build_m02_deposit.py; md5 8f2fa9f7e814ba807710480a7f60cb65, 112 files, 6,044,685 bytes). v1.0.2 — impact-first reframe (2026-08-23): the introduction and abstract reframed to lead with the applied motivation (sparse independence departures in genomics, network/text co-occurrence, pharmacovigilance, ecology, survey cross-tabulation) and the corpus calibration failure, before the detection-boundary theory. No number, theorem, figure, or dataset changed. v1.0.1 — published (2026-08-08): adds the Zenodo concept DOI to the manuscript Availability statement and CITATION.cff, and the widened Figure 8 top box. Content otherwise identical to v1.0.0. v1.0.0 ✅ 10.5281/zenodo.21844798 — first published deposit: the combined three-part manuscript, the D02 derivations, the verification and study code with fixed seeds and locked outputs, all figures, the in-browser detector, and the prior-art / adversarial / consistency audits. Provenance: every number traces to a named, deterministically-seeded script under code/; the combined manuscript is assembled by code/assemble_combined.py and built by code/build_docx.py. Related identifiers: T_root methodology 10.5281/zenodo.21522471; exact conditional engine 10.5281/zenodo.21831680.
William Dwyer· Zenodo (CERN European Organi...· 0 citations
Reproducibility package for the interval-estimate paper of the contingency-table effect-size arc, the companion to the point-estimate paper M0f. It regenerates every result behind the exact conditional confidence interval for phi^2 (and Cramer's V): the pre-registered Berger-Boos simulation (C1 passed, C2 and C3 failed) frozen before the run; the post-registration exact conditional (mid-p) interval that turns the two failures into a positive result; its characteristic-function / cosine (CF/COS) extension to larger and denser tables; the certified 2x2 coverage floor; the exact conditional median-unbiased point estimate (the fold) that resolves the residual; the shape-by-effect factorial decomposition of the small-effect coverage dip into its additive mechanisms (mid-p atom, estimand gap, discreteness residual); and the direct exact-coverage sweeps. Includes the manuscript and Additional File 1 (docx + pdf), all figures and their black-and-white-safe generators, the derivation companions, the pre-registration, a prior-art audit, the shared estimator/interval code with its exact dynamic-programming tail engines (verified to ~3e-15), and a null-coverage regression self-test. Every reported number regenerates under recorded seeds; runs are staged, resumable, and memory-capped. MIT License for code; CC BY 4.0 for documents and data.
William Dwyer· Zenodo (CERN European Organi...· 0 citations