ArticleJournal of applied statistics2022
Robust inference for skewed data in health sciences.
Article in Journal of applied statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 0 citations in OpenAlex.
- Formal and informal financial inclusion and its impact on health: empirical evidence from South Africa.Health economics review · 2026Article
- Integrative transcriptomic and single-cell analysis reveals mitochondrial-related gene biomarkers in heart failure with preserved ejection fraction.Scientific reports · 2025Article
- Assessing stroke survivors' knowledge: a scoping review of tools and influencing factors.Journal of health, population, and nutrition · 2025Article
- Oxidative DNA Damage and Repair Dynamics in Multiple Sclerosis: Insights from Comet Assay Kinetics, Base Excision Repair Gene Expression, and Genotype Analysis.Biomolecules · 2025Article
- Correlation Between Blood Coagulation Profile and Viscosity: Clinical Laboratory Observational Study.Medical sciences (Basel, Switzerland) · 2025Observational
- Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health data are often not symmetric to be adequately modeled through the usual normal distributions; most of them exhibit skewed patterns. They can indeed be modeled better through the larger family of skew-normal distributions covering both skewed and symmetric cases. Since outliers are not uncommon in complex real-life experimental datasets, a robust methodology automatically taking care of the noises in the data would be of great practical value to produce stable and more precise research insights leading to better policy formulation. In this paper, we develop a class of robust estimators and testing procedures for the family of skew-normal distributions using the minimum density power divergence approach with application to health data. In particular, a robust procedure for testing of symmetry is discussed in the presence of outliers. Two efficient computational algorithms are discussed. Besides deriving the asymptotic and robustness theory for the proposed methods, their advantages and utilities are illustrated through simulations and a couple of real-life applications for health data of athletes from Australian Institute of Sports and AIDS clinical trial data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.