プロフィール詳細

プロジェクトを作成

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☆☆☆☆☆

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☆☆☆☆☆

Yuncheng J.に依頼

Thailand

Freelance Quantitative Methodologist & Statistical Diagnostician | R, Bayesian & Predictive Modeling | Biostatistic

プロフィール概要

I am a quantitative methodologist, active peer reviewer, and researcher with an academic background in Public Health and Agronomy. I specialise in complex multivariate analysis and structural modelling. I bridge the gap between rigorous statistical theory and real-world biological, epidemiological, or social science mechanisms. I offer advanced, code-based analytics solutions to academic researchers and data science teams. My primary objective is to ensure your analytical framework withstands the strictest peer-review scrutiny and adheres to top-tier publication standards. I am fluent in both Chinese and English; you may contact me in either. My Working Principles • What I will help you with: Statistical consultation, theoretical modelling, R programming, pre-analysis data auditing, and pre-submission data forensics. • What I will NEVER do: P-hacking, data-driven post-hoc model trimming, or any statistical misconduct. I engineer robust models; I do not manufacture fake significance. • Transparency: All analyses are executed via transparent, code-based workflows (primarily in R) to guarantee absolute computational reproducibility. Core Methodological Expertise & Client Benefits • Diagnostic Auditing & Reviewer Rebuttals (My highly requested service): Stuck in the peer-review process? I routinely assist research teams by drafting mathematically grounded rebuttals and implementing post hoc methodological corrections. I provide forensic assessments of model misspecification to satisfy demanding editors and reviewers. • Publication-Grade Data Visualisation: Complex statistical realities demand precise visual translation. I engineer high-fidelity, reproducible graphics in R (e.g., mapping Bayesian posterior distributions, complex SEM path diagrams, or MCMC diagnostic trace plots). I don't just make charts; I create compelling visual evidence that satisfies high-impact journal standards and clearly communicates intricate scientific mechanisms. • Structural Equation Modelling (SEM): Specification, estimation, and validation of complex latent variable models. I help clients handle non-normal data and resolve fatal structural issues (e.g., critical collinearity, measurement redundancy) before submission. • Bayesian Data Analysis (MCMC): When traditional frequentist methods fail (particularly in small-sample contexts), I employ probabilistic programming to estimate precise posterior distributions and quantify model uncertainty. This offers a robust, publishable alternative to chasing P-values. • Monte Carlo Simulations: I design rigorous simulation studies for statistical power analysis and robust out-of-sample predictive validation to prove the reliability of your findings.

専門分野

• ★ Biostatistics
• ★ Applied Statistics
• ★ R
• ☆ Mycology/Fungi
• ☆ Data Analysis
• ☆ Data Processing
• ☆ Data Visualization
• ☆ Data Cleaning
• ☆ Statistics
• ☆ Comparative Analysis
• ☆ Social Statistics
• ☆ Regression Analysis
• ☆ Multivariate Analysis
• ☆ Bayesian Statistics
• ☆ Statistical Review
• ☆ Human Behavior & Psychology
• ☆ Human-Computer Interactions (HCI)
• ☆ Social Psychology
• ☆ Health Policy
• ☆ SQL
• ☆ Public Health
• ☆ Epidemiology
• ☆ Literature Review
• ☆ Systematic Literature Review

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Translation

Research Scientific and Technical Research

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Data Processing

職務経験

Researcher

Research Fellow

11月 2023 - 現在

学歴

PhD in Plant Pathology

Chiang Mai University - Thailand

11月 2025 - 現在

Master in Public Health

Chulalongkorn University - Thailand

11月 2023 - 4月 2025

Bachelor of Information Communication Technology

Swinburne University of Technology - Australia

2月 2012 - 11月 2015

認定資格

• 認定資格の詳細は未入力です。

出版物

CONFERENCE PAPER

Yuncheng Jia, Zixin Yong, Bo Qin (2025). Long-term PDE5 Inhibitors and Glaucoma Risk: Causal Inference and Systematic Evaluation Using Markov Models and Logistic Regression .