Selected work

Representative Papers

Testing equivalence to binary generalized linear models with application to logistic regression

Jul 16, 2026

This study addresses the problem of assessing whether observed data are “sufficiently close” to a binary generalized linear model—such as logistic regression—with fully categorical covariates, rather than requiring exact model fit. To this end, the authors propose a formal equivalence testing framework based on minimum distance methodology. The approach leverages both asymptotic theory and bootstrap procedures to compute critical values, thereby filling a critical gap left by conventional goodness-of-fit tests, which are ill-suited for evaluating practical equivalence. Through extensive simulation studies and analyses of two real-world datasets, the proposed method demonstrates strong finite-sample performance and practical utility, offering a robust tool for model adequacy assessment in applied settings.

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New Equivalence Tests for Hardy-Weinberg Equilibrium and Multiple Alleles

Jul 14, 2025

This paper addresses the underexplored problem of testing Hardy–Weinberg equilibrium (HWE) equivalence in multi-allelic settings. We propose two novel test statistics: one grounded in asymptotic distribution theory and the other employing bootstrap resampling to estimate variance—both avoiding strong assumptions about genotype frequency distributions, thereby markedly improving robustness and applicability in small samples. Our key contribution is the first rigorous, computationally feasible framework for HWE equivalence testing under multi-allelic loci. Through extensive simulations and evaluation on three real-world population genetic datasets, the proposed methods demonstrate superior control of Type I error rates and higher statistical power compared to existing tests—particularly in scenarios involving rare alleles and limited sample sizes.

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Recent publications

Latest Papers

Testing equivalence to binary generalized linear models with application to logistic regression

Jul 16, 2026

This study addresses the problem of assessing whether observed data are “sufficiently close” to a binary generalized linear model—such as logistic regression—with fully categorical covariates, rather than requiring exact model fit. To this end, the authors propose a formal equivalence testing framework based on minimum distance methodology. The approach leverages both asymptotic theory and bootstrap procedures to compute critical values, thereby filling a critical gap left by conventional goodness-of-fit tests, which are ill-suited for evaluating practical equivalence. Through extensive simulation studies and analyses of two real-world datasets, the proposed method demonstrates strong finite-sample performance and practical utility, offering a robust tool for model adequacy assessment in applied settings.

0 citationsRead paper

New Equivalence Tests for Hardy-Weinberg Equilibrium and Multiple Alleles

Jul 14, 2025

This paper addresses the underexplored problem of testing Hardy–Weinberg equilibrium (HWE) equivalence in multi-allelic settings. We propose two novel test statistics: one grounded in asymptotic distribution theory and the other employing bootstrap resampling to estimate variance—both avoiding strong assumptions about genotype frequency distributions, thereby markedly improving robustness and applicability in small samples. Our key contribution is the first rigorous, computationally feasible framework for HWE equivalence testing under multi-allelic loci. Through extensive simulations and evaluation on three real-world population genetic datasets, the proposed methods demonstrate superior control of Type I error rates and higher statistical power compared to existing tests—particularly in scenarios involving rare alleles and limited sample sizes.

0 citationsRead paper