影片地圖
這裡的每一支影片都是從某一章的「延伸觀看」蒐集來的,附上它在哪一章被推薦。清單由各頁自動彙整,不另外手動維護,所以不會和章節推薦的內容脫節。
中文影片
Principles of Epidemiology 03. Disease Occurrence and Prototype of Study Designs出自 怎麼讀一篇臨床研究論文
Principles of Epidemiology 08. Case-Control Study 1: Principles出自 病例對照研究
Principles of Epidemiology 09. Case-Control Study 2: M-H Methods & Selection Bias出自 病例對照研究
臨床試驗 01. 課程簡介出自 隨機對照試驗
文獻搜尋 – Cochrane Library + PubMed出自 系統性回顧與統合分析
如何選擇一個統合分析的研究題目出自 系統性回顧與統合分析
用 AI 做臨床研究:做出論文第一張表 Table 1|該不該放 p 值?改用 SMD
AI 臨床研究實戰 EP6|Table 1 基線特徵表怎麼做:p 值的陷阱、常態性檢定、缺失值
醫學統計 EP10 t 檢定與非參數法出自 t 檢定與變異數分析
醫學統計 EP11 ANOVA出自 t 檢定與變異數分析
醫學統計 EP04 標準差與標準誤出自 t 檢定與變異數分析
生物統計學一 45.【型一與型二錯誤】出自 t 檢定與變異數分析
醫學統計 EP12 卡方檢定
醫學統計 EP15 RR vs OR
醫學統計 EP02 變數類型
醫學統計 EP13 線性迴歸出自 線性迴歸
生物統計學一 93.【迴歸分析 (1)】Simple Linear Regression Model出自 線性迴歸
Lec04 統計學(二) Ch11.1-11.5 簡單廻歸分析與相關分析出自 線性迴歸
醫學統計 EP14 羅吉斯迴歸出自 邏輯迴歸與勝算比
【Hands-on】L9 R: Logistic Regression出自 邏輯迴歸與勝算比
【Lecture】L12 Generalized Linear Model (1)
存活分析(Survival Analysis)
【Lecture】L19 Survival Analysis (1)
醫學統計 EP16 存活分析:解讀階梯狀 KM 曲線與風險比率
如何看懂 K-M 存活曲線:以 FLAURA 研究為例
存活分析(Survival Analysis)第二部分出自 Cox 比例風險模型
【Lecture】L20 Survival Analysis (2)
【Hands-on】L12 R:Survival Analysis出自 時間相依共變項
醫學統計 EP17 敏感度、特異度與預測值
Principles of Epidemiology 10. Diagnosis, Tests, and Screening
實證醫學-診斷與篩檢出自 預測值與盛行率
好想告訴你的醫學統計-敏感性、特異性、陽性預測值與陽性概似比
ROC 系列 1/6:ROC 曲線是什麼出自 ROC 曲線與 AUC
ROC 系列 4/6:AUC 的兩大臨床陷阱出自 ROC 曲線與 AUC
ROC 系列 5/6:最佳切點與代價權衡
ROC 系列 6/6:罕見疾病與過度樂觀陷阱
AI 臨床研究實戰 EP7|預測 vs 分類、Data Leakage、Propensity Score出自 變數選擇
SEER 數據之臨床預測模型 課時10 模型驗證出自 內部驗證與樂觀偏誤
SEER 數據之臨床預測模型 課時09 利用校準圖評價模型出自 校準
因果圖 DAG 是什麼?一張圖看穿因果的陷阱
Principles of Epidemiology 05. Causal Inferences, Bias, Confounding, and Interaction
資料小探 – 傾向分數配對法出自 傾向分數配對
Outcome research: Causal inference & Propensity score II 傾向分數出自 傾向分數配對
工具變數 (instrumental variables)出自 工具變數
【Biostatistics Corner】Meta-analysis 基礎篇出自 效果量與變異數
醫學統計 EP18 統合分析:加權整合多項研究、看懂森林圖出自 固定效應與隨機效應
統合分析的異質性(Heterogeneity)
統合分析異質性和小樣本研究偏誤
為什麼傳遞性假設對網絡統合分析很重要?
利用 Stata 進行網絡統合分析
使用 SUCRA 進行網絡統合分析治療排名
元件網絡統合分析簡介英文影片
Types of Study Designs in Clinical Research Explained & Made Easy出自 怎麼讀一篇臨床研究論文
Cohort Studies: A Brief Overview出自 世代研究
Cohort study vs case-control study: everything you need to know in 5min出自 世代研究
Case-Control Studies: A Brief Overview出自 病例對照研究
Case-control study explained出自 病例對照研究
Randomized control trial (RCT) explained出自 隨機對照試驗
Intention-to-treat analysis: What is it and why is it important?出自 隨機對照試驗
Hazard Ratios – Best explanation for beginners出自 預測模型研究
COX REGRESSION and HAZARD RATIOS出自 預測模型研究
Narrative vs systematic vs scoping review出自 系統性回顧與統合分析
How To Conduct A Systematic Review and Write-Up in 7 Steps (PRISMA, PICO)出自 系統性回顧與統合分析
How to Critically Appraise a Systematic Review: Part 1出自 系統性回顧與統合分析
[R tutorial EP1] How to make baseline characteristics table / Table1
Table 1 in R with gtsummary
The Main Ideas of Fitting a Line to Data出自 線性迴歸
StatQuest: Logistic Regression出自 邏輯迴歸與勝算比
Logistic Regression Details Pt1: Coefficients出自 邏輯迴歸與勝算比
Explaining generalized linear models (GLMs)
Censoring and Truncation [Survival Analysis 2/8]
Survival Analysis [Simply Explained]
Kaplan-Meier-Curve [Simply Explained]
Cox Regression [Cox Proportional Hazards]出自 Cox 比例風險模型
The Cox proportional hazards model explained
Survival Analysis Part 9 | Cox Proportional Hazards Model
Cox Proportional Hazard Models
COMPETING RISK EXPLAINED
Competing Risk Analysis
Easily Perform Competing Risks Survival Analysis with SAS Studio
The Statistics of Life and Death | Survival Analysis出自 時間相依共變項
Sensitivity and specificity – explained in 3 minutes
Calculating Sensitivity and Specificity using a 2x2 table
Machine Learning Fundamentals: Sensitivity and Specificity
Sensitivity, Specificity, PPV, NPV出自 預測值與盛行率
Sensitivity and Specificity Explained Clearly (Biostatistics)出自 預測值與盛行率
What Are Likelihood Ratios and How Are They Used
Likelihood Ratios Explained
Likelihood Ratios and The Probability of Diagnosis
Diagnosis 03: Likelihood Ratios
ROC and AUC, Clearly Explained!出自 ROC 曲線與 AUC
How to interpret ROC curves出自 ROC 曲線與 AUC
ROC Curves and Area Under the Curve (AUC) Explained出自 ROC 曲線與 AUC
ROC Curves
Biostatistics – All You Need To Know About The ROC Curve
What Are Clinical Prediction Rules?出自 變數選擇
Key Steps and Common Pitfalls in Clinical Prediction Model Research出自 變數選擇
Prediction model, discrimination, calibration, overfitting, validation出自 收縮與懲罰迴歸
Building and validating prediction models出自 收縮與懲罰迴歸
Sample size calculations for clinical prediction model research
RSS Seminar with Richard Riley
VALIDATING PREDICTION MODELS – what is discrimination and calibration?出自 外部驗證
Karel Moons | Validating Medical Predictive Models | Philosophy of Data Science出自 外部驗證
Clearing Up Confounding
Introduction to Causal Graphs
Directed Acyclic Graphs (DAGs)
Propensity scores: Everything you need to know in 5min出自 傾向分數配對
How Propensity Scores Work | NEJM Evidence出自 傾向分數配對
Propensity score matching: an introduction出自 傾向分數配對
6.4 – Propensity Scores and Inverse Probability Weighting (IPW)出自 逆機率加權
Estimating Causal Effects: Inverse Probability Weighting出自 逆機率加權
INSTRUMENTAL VARIABLE ANALYSES EXPLAINED出自 工具變數
The Logic of Instrumental Variables出自 工具變數
The 3 Instrumental Variables Assumptions出自 工具變數
Introduction to Instrumental Variables (IV)出自 工具變數
Understand What a Meta-Analysis is in Less Than 5 Minutes出自 效果量與變異數
An Introduction to Systematic Review and Meta-analysis出自 效果量與變異數
Systematic reviews and meta analysis出自 固定效應與隨機效應
How to do your first meta-analysis from start to finish出自 固定效應與隨機效應
What is Heterogeneity?
How to Interpret a Forest Plot
Confounding, chance, and bias出自 選擇偏誤