Bilingual epidemiology curriculum · 双语流行病学课程

Learn epidemiology as a way of thinking.

把流行病学学成一种思考方式。

Follow the full chain from population patterns and study design to bias, causal interpretation, and reproducible analysis in R. 从人群疾病模式与研究设计出发,系统学习偏倚、因果解释以及可重复的 R 分析。

See the field as one connected system.

Epidemiology links a population question to a defensible measure, a study design, an analysis, and a carefully bounded conclusion. 流行病学把人群问题、合理指标、研究设计、统计分析和审慎结论连接成一条完整证据链。

Measure frequency

Distinguish prevalence, cumulative incidence, incidence rate, risk, odds, person-time, and mortality measures.

Choose a design

Match descriptive, cross-sectional, cohort, case-control, ecological, and experimental designs to the research question.

Protect validity

Recognize selection bias, information bias, confounding, random error, effect modification, and limits to generalizability.

Interpret evidence

Read estimates, confidence intervals, screening metrics, and causal claims without overstating what the data can support.

A route from question to evidence.

Use this sequence for a first pass through the guides, then return to individual sections when planning or reviewing a study. 初学时可按此顺序阅读;设计或评审研究时,再把每一部分当作随时可查的参考。

  1. 01

    Frame the question

    Specify the population, exposure, comparison, outcome, time, and purpose of the study.

    Choose an edition
  2. 02

    Describe the pattern

    Ask who is affected, where, when, and how often before moving to explanations.

    Open the English guide
  3. 03

    Build the comparison

    Select a design and comparison group that can answer the question with minimal avoidable bias.

    打开中文教程
  4. 04

    Estimate and assess

    Calculate measures of association and examine chance, bias, confounding, and model assumptions.

    Explore research questions
  5. 05

    Communicate limits

    Report the estimate, uncertainty, assumptions, relevance, and remaining uncertainty—not just a verdict.

    Read our principles

Choose your guide.

Start with epidemiologic foundations, use the research-design module to build a defensible protocol, then continue to advanced methods for complex data and causal questions. 先学习流行病学基础,再通过研究设计专题形成合理方案,最后用进阶方法处理复杂数据与因果问题。

01
Beginner Foundations Applied R

Foundations of Epidemiology

流行病学基础、方法与常见研究

A detailed guide to concepts, measures, study designs, research questions, screening, outbreaks, causal inference, and reproducible analysis.

Frequency measures · association · study design · bias · confounding · screening · outbreaks · causal thinking

02
Beginner–Intermediate Sampling Protocol

Epidemiologic Research Designs

流行病学研究设计、研究类型、抽样与方案制定

An end-to-end guide to selecting study types, defining source and study populations, sampling participants, minimizing bias, and turning a question into an ethical, analyzable protocol.

Design choice · target population · sampling frames · sample size · recruitment · protocol · ethics · analysis planning

03
Intermediate–Advanced Causal Inference Applied R

Advanced Epidemiologic Methods

进阶流行病学方法

A practical guide to time-to-event and competing-risk data, modern causal estimation, missing-data methods, transportability, and bias analysis.

Survival · competing risks · causal estimation · missing data · transportability · bias analysis

Common research, organized by purpose.

A method becomes useful only after the research purpose is clear. These recurring question types provide a practical map of the field. 先明确研究目的,再选择方法。以下常见问题类型构成了一张实用的流行病学研究地图。

Learn the reasoning—not just the formula.

The V Lab tutorials treat epidemiology as disciplined reasoning under uncertainty. Code supports the argument; it does not replace design knowledge or scientific judgment. The V Lab 将流行病学视为在不确定性下进行的严谨推理:代码用于支撑论证,而不能取代研究设计知识与科学判断。

Question before method 先定义人群、时间与目标,再选择指标、设计和模型。
Estimates with uncertainty 同时报告效应大小、区间估计、假设与局限,而不只报告显著性。
Reproducibility with responsibility 让分析可检查、可复现,并把伦理、公平与隐私纳入研究全过程。