経済学における実験実験の複製性を評価する
Colin F Camerer1, Anna Dreber2, Eskil Forsell2
1Division of Humanities and Social Sciences, California Institute of Technology, 1200 East California Boulevard, MC 228-77, Pasadena, CA 91125, USA.
まとめ
18の経済学の研究を複製すると 61%が有意な結果を示した. 平均的な複製効果の大きさは,元の66%で,経済研究における適度な複製性を示している.
科学分野:
- 経済学
- 経済学
- 科学的複製
背景:
- 科学的発見の複製可能性に関する最近の懸念
- 経済学の分野における複製性に関する経験的データの必要性
研究 の 目的:
- トップ経済学誌に掲載された経験的研究の複製性を評価する.
- 経済研究の再現性に関する定量的な証拠を提供すること.
主な方法:
- アメリカン・エコノミック・レビューとクォーターリー・ジャーナル・オブ・エコノミクス (2011年~2014年) の18件の研究を複製したものです.
- 各複製に対して,事前に定義された,一般に利用可能な分析計画を使用する.
- すべてのレプリケーションは,5%の有意度レベルでのオリジナルの効果サイズを検出するために少なくとも90%の統計力を持っていたことを保証します.
主要な成果:
- 元の方向での有意な効果は,18件のうち11件で確認された (61%).
- 成功した複製の平均効果は,最初に報告された効果の66%でした.
- 予測市場を含む追加の複製性指標は67%から78%の割合を示した.
結論:
- 経済的研究の大部分は 適度な複製性を示しています
- この発見は,経済学における科学的再現性に関する議論に,経験的証拠を寄与しています.
- この研究では,透明な分析計画と信頼性の高い研究成果を確保するための十分な統計力の重要性を強調しています.
さらに関連する動画
関連する概念動画
What is an Experiment?
19.7K
An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
19.7K
Randomized Experiments
9.3K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
9.3K
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
380
Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
380
Econometric Views (EViews)
665
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
665
Mechanistic Models: Compartment Models in Individual and Population Analysis
321
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
321
Uncertainty in Measurement: Accuracy and Precision
113.5K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
113.5K


