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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 王道一 | zh_TW |
dc.contributor.advisor | Joseph Tao-yi Wang | en |
dc.contributor.author | 翁維謙 | zh_TW |
dc.contributor.author | Wei-Chien Weng | en |
dc.date.accessioned | 2024-06-04T16:08:27Z | - |
dc.date.available | 2024-06-05 | - |
dc.date.copyright | 2024-06-04 | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-05-24 | - |
dc.identifier.citation | 1. Brodeur, A., M. Lé, M. Sangnier, and Y. Zylberberg (2016). Star wars: The empirics strike back. American Economic Journal: Applied Economics 8(1), 1–32.
2. Brodeur, A., D. Mikola, N. Cook, T. Brailey, R. Briggs, A. de Gendre, Y. Dupraz, L. Fiala, J. Gabani, R. Gauriot, et al. (2024). Mass reproducibility and replicability: A new hope. I4R Discussion Paper Series. 3. Camerer, C. F., A. Dreber, E. Forsell, T.-H. Ho, J. Huber, M. Johannesson, M. Kirchler, J. Almenberg, A. Altmejd, T. Chan, et al. (2016). Evaluating replicability of laboratory experiments in economics. Science 351(6280), 1433–1436. 4. Davis, A. M., B. Flicker, K. Hyndman, E. Katok, S. Keppler, S. Leider, X. Long, and J. D. Tong (2023). A replication study of operations management experiments in Management Science. Management Science 69(9), 4977–4991. 5. De Long, J. B. and K. Lang (1992). Are all economic hypotheses false? Journal of Political Economy 100(6), 1257–1272. 6. Fišar, M., B. Greiner, C. Huber, E. Katok, A. I. Ozkes, and Management Science Reproducibility Collaboration (2024). Reproducibility in Management Science. Management Science 70(3), 1343–1356. 7. He, L. (2024). Email correspondence regarding replication report (Wang and Weng, 2024). February 26. 8. He, L., P. P. Analytis, and S. Bhatia (2022). The wisdom of model crowds. Management Science 68(5), 3635–3659. 9. Loewenstein, G., T. O’Donoghue, and S. Bhatia (2015). Modeling the interplay between affect and deliberation. Decision 2(2), 55. 10. Loomes, G. and R. Sugden (1982). Regret theory: An alternative theory of rational choice under uncertainty. The Economic Journal 92(368), 805–824. 11. Nagel, S. (2018). Code-sharing policy: Update. Journal of Finance: Editor Blog. (March 6) https://voices.uchicago.edu/jfeditor/2018/03/06/code-sharing-policy-update. 12. Viscusi, W. K. (1989). Prospective reference theory: Toward an explanation of the paradoxes. Journal of Risk and Uncertainty 2, 235–263. 13. Wang, J. T. Y. and W. C. Weng (2024). The wisdom of model crowds only working on mixed domain lotteries. Replication Report for “The Wisdom of Model Crowds”. | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92682 | - |
dc.description.abstract | 在期刊強制要求資料與程式需公開後,Fišar et al. (2024) 發現論文結果的可重現性上升。作為互補,本文提出一種快速檢驗計算密集論文結果可否重現的方法,並以 He et al. (2022) 作為示範。該研究以每位受試者的資料,分別估計 58 個重要的風險選擇模型,並發現模型集群的預測表現優於最佳個體模型。使用原作者提供的資料與程式,我們無法重現該篇文章的結果,因為原作者程式有隱藏的錯誤導致模型集群具有較大的標準誤差。改用少部分樣本跑同樣的分析不僅能迅速抓到隱藏的程式錯誤,還可以穩健地重現原作者的主要發現。因此,期刊可採用類似的指導方針檢驗其他研究結果的重現性,毋須擔心成本過高。 | zh_TW |
dc.description.abstract | Complementing the recent finding that Data and Code Disclosure policy increases the reproducibility rate in Fišar et al. (2024), this comment demonstrates a time-saving workaround to conduct computationally intensive reproductions. We take He et al. (2022) as an illustrative example, which estimates 58 prominent models of risky choice at the subject level to show that model crowds outperform the aggregate best individual model. Employing raw data and code from their replication package, we cannot reproduce the main result, since the model crowds generate much larger standard errors due to a hidden coding error. Our robustness replication with only a small fraction of the data not only catches this coding error, but successfully replicates the original finding with high power. Therefore, journals can adopt a similar paradigm as the guideline to examine computational reproducibility at a manageable cost. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-06-04T16:08:26Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2024-06-04T16:08:27Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 中文摘要 iii 英文摘要 iv 第一章 Introduction 1 第二章 Computational Reproduction 4 第一節 Matlab Estimation 4 第二節 Running R on Intermediate Data 7 第三章 Hidden Coding Error Corrections 8 第四章 Implications for Data and Code Disclosure Policy 12 第五章 Conclusion 16 參考文獻 References 17 附錄 19 第一節 Additional Tables and Figures 19 第二節 Details in Coding, Computational Reproduction, and Robustness Replication 26 第三節 Computational Reproduction of Section 2 34 第四節 Computational Reproduction of Section 3 48 第五節 Computational Reproduction Using σ = λ in Matlab Estimation 62 | - |
dc.language.iso | en | - |
dc.title | 開放科學的實踐:檢驗計算密集論文結果可否重現的省時方法 | zh_TW |
dc.title | Enforcing Open Science: A Time-saving Test for Computationally Intensive Reproductions | en |
dc.type | Thesis | - |
dc.date.schoolyear | 112-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 林明仁;陳慶池;黃景沂;黃從仁 | zh_TW |
dc.contributor.oralexamcommittee | Ming-Jen Lin;Jimmy Hing Chi Chan;Ching-I Huang;Tsung-Ren Huang | en |
dc.subject.keyword | 個體決策,十倍交叉驗證法,模型組合,重現性檢驗,重複抽樣, | zh_TW |
dc.subject.keyword | Decision Making,10-fold Cross-validation,Model Ensembles,Computational Reproduction,Resampling, | en |
dc.relation.page | 75 | - |
dc.identifier.doi | 10.6342/NTU202400992 | - |
dc.rights.note | 同意授權(全球公開) | - |
dc.date.accepted | 2024-05-27 | - |
dc.contributor.author-college | 社會科學院 | - |
dc.contributor.author-dept | 經濟學系 | - |
顯示於系所單位: | 經濟學系 |
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