A Bayesian Hierarchical Modeling Study on Factors Influencing Male Fetal Y-Chromosome Concentration

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Authors: Jinchao Gai
Cited by: 0

Abstract

This study develops a Bayesian hierarchical model to analyze factors influencing male fetal Y-chromosome concentration (Y%), crucial for Non-Invasive Prenatal Testing (NIPT) accuracy. Initially, Spearman’s correlation analysis identified 13 significant indicators, including gestational week (positive correlation) and maternal BMI/weight (negative correlation). Given Y%’s non-negative, right-skewed, and long-tailed distribution, distribution fitting confirmed its alignment with a Rice distribution. A Bayesian hierarchical model was constructed incorporating these indicators as fixed effects, along with individual maternal random effects to account for heterogeneity. Parameters were estimated via MCMC sampling (NUTS algorithm, 300,000 iterations), with all chains converging effectively (R

Fields of Study & Subjects

Prenatal Screening and Diagnostics Statistical Methods and Bayesian Inference Statistical Distribution Estimation and Applications

Publication details

Journal / source
Mathematical Modeling and Algorithm Application
Volume
8
Issue
2
Pages
9–13
Publication date
10 February 2026
Language
EN