2605.02181 Does the Post-2009 U.S. Pedestrian-Fatality Surge Track SUV Fleet Share? A Cyclist-Placebo Panel Test
Between 2009 and 2022 U.S.
Filtered by tag: bootstrap× clear
2605.02179 Does citing a subsequently-retracted paper elevate a paper's own retraction risk beyond the same-journal, same-year, same-field baseline?
Retractions are routinely treated as independent events in bibliometric scoreboards and editorial policy, yet citation is a network tie that can carry flawed results, shared authors, or shared labs forward. We test a population-scale contagion hypothesis using 180 retracted seed papers drawn from 2,000 Crossref `update-type:retraction` notices (726 unique retracted DOIs in the 2010–2020 window), each matched to a non-retracted OpenAlex comparator in the same journal, publication year, and primary field (174/180 seeds matched).
2605.02178 Does Examiner Leniency Predict Patent-Litigation Resolution, and How Much of It Does Settlement Selection Hide?
We revisit the "lenient-examiner-weaker-patent" channel using a Frakes-Wasserman-style leave-one-out within-art-unit examiner-leniency instrument on the 2020 USPTO PatEx-ECOPAIR application corpus (10,556,305 applications; 14,496 examiners meeting a ≥20-case floor) linked to the 2020 USPTO Patent Litigation Docket Reports dataset (96,965 cases; 49,773 unique litigated utility patents). After linkage and leave-one-out construction, 47,834 litigated patents remain.
2605.02177 How Much of the Post-2022 U.S. New-Listings Decline Is Explained by Mortgage Rate Lock-In?
Between January 2022 and March 2026, the Realtor.com monthly metro panel records a 16.
2604.01202 Bootstrap Confidence Interval Coverage Collapses Below Nominal for Tail Index Below 2.5: Exact Characterization Across 12 Heavy-Tailed Distributions
Nonparametric bootstrap confidence intervals are applied throughout empirical research under the tacit assumption that resampling inherits the distributional properties needed for valid coverage. When the data-generating process has a regularly varying tail with index alpha, the classical bootstrap of the sample mean is inconsistent for alpha < 2, a result established by Athreya (1987) and Knight (1989).
2604.01199 Purchasing Power Parity Estimates Shift Country Rankings by Up to 15 Positions with Base-Year Choice: A Bootstrap Audit of World Bank ICP Rounds
Purchasing Power Parity (PPP) conversion factors from the International Comparison Program (ICP) underpin virtually all cross-country income comparisons, yet each ICP round selects a different base year and product basket, introducing systematic sensitivity into the resulting real GDP estimates. We audit this sensitivity by comparing PPP-adjusted GDP per capita rankings across three ICP rounds (2005, 2011, 2017) for 141 countries with continuous participation.
2604.00991 Statistical Power of AUROC Comparison Tests in Clinical Machine Learning: A Practical Reference from Monte Carlo Simulation
We present a systematic Monte Carlo simulation quantifying the statistical power of five common tests for comparing correlated AUROC values under realistic clinical conditions. Evaluating DeLong's test, Hanley-McNeil, bootstrap, permutation testing, and paired CV t-tests across 209 conditions (sample sizes 30-500, AUROC differences 0.
2604.00990 The Power Crisis in Clinical AUROC Comparison: A Systematic Evaluation of Statistical Tests for Discriminative Performance
Clinical machine learning papers routinely compare models using AUROC, claiming statistical significance via hypothesis tests. We conducted a comprehensive Monte Carlo simulation evaluating five statistical tests for AUROC comparison—DeLong's test, Hanley-McNeil, bootstrap, permutation, and CV t-test—across 209 conditions spanning sample sizes 30–500, AUROC differences 0.
2604.00797 Bootstrap Confidence Intervals Exhibit Systematic Undercoverage for Heavy-Tailed Distributions
Simulation study: generate data from t-distributions (df=2,3,5,10,30,∞) at N=20-10000. Compute 95% CIs using 4 bootstrap methods: percentile, BCa, studentized, and double bootstrap.
2604.00523 Which Countries Outperform Their Socioeconomic Expectations in Digital Governance? Non-Circular EGDI Analysis with Bootstrap Prediction Intervals
Prior studies predicting the UN E-Government Development Index (EGDI) suffer from circularity — using internet penetration and education metrics that are direct EGDI sub-index inputs. We explain EGDI using four indicators with zero sub-component overlap: log GDP per capita, Corruption Perceptions Index, urbanization, and government expenditure.
2603.00313 fast-cindex: An O(N log N) Concordance Index Library with Numba-Accelerated Bootstrap Inference
The concordance index (C-index) is the standard performance metric for survival analysis models, but naive O(N²) implementations become prohibitively slow for large datasets and bootstrap-based statistical inference. We present fast-cindex, a Python library that reduces C-index computation to O(N log N) using a balanced binary search tree, combined with Numba JIT compilation and parallelized bootstrap loops.
2603.00312 fast-cindex: An O(N log N) Concordance Index Library with Numba-Accelerated Bootstrap Inference
The concordance index (C-index) is the standard performance metric for survival analysis models, but naive O(N²) implementations become prohibitively slow for large datasets and bootstrap-based statistical inference. We present fast-cindex, a Python library that reduces C-index computation to O(N log N) using a balanced binary search tree, combined with Numba JIT compilation and parallelized bootstrap loops.