|
課程名稱 |
高等統合分析方法
Advanced Aanalytical Methods for Meta-analysis |
|
開課學期 |
111-2 |
|
授課對象 |
共同教育中心 統計碩士學位學程 |
|
授課教師 |
杜裕康 |
|
課號 |
EPM7014 |
|
課程識別碼 |
849EM0980 |
|
班次 |
|
|
學分 |
2.0 |
|
全/半年 |
半年 |
|
必/選修 |
選修 |
|
上課時間 |
星期二6,7(13:20~15:10) |
|
上課地點 |
公衛214 |
|
備註 |
本課程以英語授課。不接受旁聽。課程將會錄影，並在課程結束後上傳至網路。電腦軟體應用：R系統。生醫領域選修課程。與何傑明合授
總人數上限：50人 |
|
|
|
|
課程簡介影片 |
|
|
核心能力關聯 |
核心能力與課程規劃關聯圖 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
本課程假定熟悉標準的統合分析方法，包括做文獻回顧、評估誤差風險等，以及標準的數據分析工具，如隨機效應模型，並強調更先進、最近開發或可用於標準統合分析方法不適用情況的分析方法。 該方法是概念性和實踐性的，從概念上激發出新方法，並介紹它們所依據的統計模型和可以用來做這些分析的軟體。統計軟體R將在實作課程中使用，因此熟悉R是一個先決條件。 |
|
課程目標 |
在修習本課程之後，學生將能：
1.針對各種情況，在多種方法中選擇統合分析方法。
2.應用這些方法並解釋其結果。
3.閱讀和討論統合分析方法的高等文獻。
4.使用R軟件進行高等統合分析，如網絡統合分析、劑量反應統合分析或診斷工具表現的統合分析。 |
|
課程要求 |
已修習過EPM5053系統性回顧及統合分析或授課教師許可。熟悉一些貝氏方法會有所幫助。 |
|
預期每週課後學習時數 |
|
|
Office Hours |
另約時間 |
|
指定閱讀 |
Harrer M, Cuijpers P, Furukawa T, Ebert D. Doing Meta-Analysis with R: A Hands-on Guide. Free e-book, URL: https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/ |
|
參考書目 |
1. Caro JJ, Ishak KJ (2010). No head-to-head trial?: Simulate the missing arms. Pharmacoeconomics, 28, 957–967.
2. Chaimani A, Salanti G, Leucht S, Geddes JR, & Cipriani A. Common pitfalls and mistakes in the set-up, analysis and interpretation of results in network meta-analysis: what clinicians should look for in a published article. Evidence-Based Mental Health, 2017; 20(3): 88-94.
3. Crippa, A., Discacciati, A., Bottai, M., Spiegelman, D., Orsini, N. (2019). One-stage dose–response meta-analysis for aggregated data. Statistical Methods in Medical Research, 28(5), 1579–1596.
4. Dahabreh IJ, Petito LC, Robertson SE, Hernán MA, Steingrimsson JA (2020). Toward causally interpretable meta-analysis: Transporting inferences from multiple randomized trials to a new target population. Epidemiology. 2020;31(3):334-344.
5. Dahabreh IJ, Robertson SE, Petito LC, Hernán MA, Steingrimsson JA (2020). Efficient and robust methods for causally interpretable meta-analysis: transporting inferences from multiple randomized trials to a target population. arXiv preprint arXiv:1908.09230
6. Greenland, S., Longnecker, M. P. (1992). Methods for trend estimation from summarized dose response data, with applications to meta-analysis. American Journal of Epidemiology, 135(11), 1301-1309.
7. Harbord RM, Deeks JJ, Egger M, Whiting P, Sterne JA. A unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics. 2007;8(2):239-51
8. Mavridis D, Myrsini Giannatsi M, Cipriani A, Salanti G. A primer on network meta-analysis with emphasis on mental health. Evidence Based Mental Health. 2015; 18(2): 40-46.
9. Nyaga VN et al. ANOVA model for network meta-analysis of diagnostic test accuracy data. Statistical Methods for Medical Research 2018; 27; 1766-1784.
10. Orsini, N., Li, R., Wolk, A., Khudyakov, P., Spiegelman, D. (2012). Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software. American Journal of Epidemiology, 175(1), 66-73.
11. Phillippo DM, Dias S, Ades AE, Belger M, Brnabic A, Schacht A, Saure D, Kadziola Z, Welton NJ (2020). Multilevel network meta-regression for population-adjusted treatment comparisons. J. R. Statist. Soc. A, 183, Part 3, pp. 1189–1210
12. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol. 2005;58(10):982-90.
13. Rücker G, Petropoulou M, Schwarzer G (2020). Network meta-analysis of multicomponent interventions. Biometrical Journal, 62:808--821
14. Shih MC, Tu YK. Evaluating network meta-analysis and inconsistency using arm‐parameterized model in structural equation modeling. Research Synthesis Methods, 2019; 10(2): 240-254.
15. Signorovitch JE, Wu EQ, Yu AP, Gerrits CM, Kantor E, Bao Y, Gupta SR, Mulani PM (2010). Comparative effectiveness without head-to-head trials. Pharmacoeconomics; 28 (10): 935-945
16. Tu YK, Wu YC. Using structural equation modeling for network meta-analysis. BMC Medical Research Methodology, 2017; 17: 104.
17. Veroniki AA et al. Evaluating multiple diagnostic tests: An application to cervical cancer. HJOG; 2021:; 20: 11-24.
18. Welton NJ, Caldwell DM, Adamopoulos E, Vedhara K (2009). Mixed treatment comparison meta-analysis of complex interventions: psychological interventions in coronary heart disease. American Journal of Epidemiology, 169:1158--1165 |
|
評量方式
(僅供參考) |
|
No. |
項目 |
百分比 |
說明 |
|
1. |
期中報告 |
40% |
|
2. |
期末考試 |
40% |
|
3. |
課堂表現 |
20% |
|
|
|
針對學生困難提供學生調整方式 |
|
上課形式 |
以錄音輔助 |
|
作業繳交方式 |
|
|
考試形式 |
|
|
其他 |
|
|
|