Toward More Transparency in Statistical Practice
Author
Abstract
Suggested Citation
DOI: 10.31219/osf.io/t93cg
Download full text from publisher
References listed on IDEAS
- Gelman A. & Pasarica C. & Dodhia R., 2002. "Lets Practice What We Preach: Turning Tables into Graphs," The American Statistician, American Statistical Association, vol. 56, pages 121-130, May.
- Susan Athey & Guido W. Imbens, 2019. "Machine Learning Methods That Economists Should Know About," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 685-725, August.
- Blakeley B. McShane & David Gal & Andrew Gelman & Christian Robert & Jennifer L. Tackett, 2019. "Abandon Statistical Significance," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 235-245, March.
- Levine, Ross & Renelt, David, 1992.
"A Sensitivity Analysis of Cross-Country Growth Regressions,"
American Economic Review, American Economic Association, vol. 82(4), pages 942-963, September.
- Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
- Tracey L Weissgerber & Natasa M Milic & Stacey J Winham & Vesna D Garovic, 2015. "Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm," PLOS Biology, Public Library of Science, vol. 13(4), pages 1-10, April.
- Darren B Taichman & Peush Sahni & Anja Pinborg & Larry Peiperl & Christine Laine & Astrid James & Sung-Tae Hong & Abraham Haileamlak & Laragh Gollogly & Fiona Godlee & Frank A Frizelle & Fernando Flor, 2017. "Data Sharing Statements for Clinical Trials: A Requirement of the International Committee of Medical Journal Editors," PLOS Medicine, Public Library of Science, vol. 14(6), pages 1-3, June.
- Noah N. N. van Dongen & Johnny B. van Doorn & Quentin F. Gronau & Don van Ravenzwaaij & Rink Hoekstra & Matthias N. Haucke & Daniel Lakens & Christian Hennig & Richard D. Morey & Saskia Homer & Andrew, 2019. "Multiple Perspectives on Inference for Two Simple Statistical Scenarios," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 328-339, March.
- Athey, Susan & Imbens, Guido W., 2019.
"Machine Learning Methods Economists Should Know About,"
Research Papers
3776, Stanford University, Graduate School of Business.
- Susan Athey & Guido Imbens, 2019. "Machine Learning Methods Economists Should Know About," Papers 1903.10075, arXiv.org.
- Uri Simonsohn & Joseph P. Simmons & Leif D. Nelson, 2020. "Specification curve analysis," Nature Human Behaviour, Nature, vol. 4(11), pages 1208-1214, November.
- Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
- Jonah Gabry & Daniel Simpson & Aki Vehtari & Michael Betancourt & Andrew Gelman, 2019. "Visualization in Bayesian workflow," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 389-402, February.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Bennett, Davara L. & Webb, Calum J.R. & Mason, Kate E. & Schlüter, Daniela K. & Fahy, Katie & Alexiou, Alexandros & Wickham, Sophie & Barr, Ben & Taylor-Robinson, David, 2021. "Funding for preventative Children’s Services and rates of children becoming looked after: A natural experiment using longitudinal area-level data in England," Children and Youth Services Review, Elsevier, vol. 131(C).
- Sacker, Amanda & Lacey, Rebecca E. & Maughan, Barbara & Murray, Emily T., 2022. "Out-of-home care in childhood and socio-economic functioning in adulthood: ONS Longitudinal study 1971–2011," Children and Youth Services Review, Elsevier, vol. 132(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Eric-Jan Wagenmakers & Alexandra Sarafoglou & Sil Aarts & Casper Albers & Johannes Algermissen & Štěpán Bahník & Noah Dongen & Rink Hoekstra & David Moreau & Don Ravenzwaaij & Aljaž Sluga & Franziska , 2021. "Seven steps toward more transparency in statistical practice," Nature Human Behaviour, Nature, vol. 5(11), pages 1473-1480, November.
- Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
- Gabriel Okasa & Kenneth A. Younge, 2022. "Sample Fit Reliability," Papers 2209.06631, arXiv.org.
- Sophie-Charlotte Klose & Johannes Lederer, 2020. "A Pipeline for Variable Selection and False Discovery Rate Control With an Application in Labor Economics," Papers 2006.12296, arXiv.org, revised Jun 2020.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ay, Jean-Sauveur & Le Gallo, Julie, 2021.
"The Signaling Values of Nested Wine Names,"
Working Papers
321851, American Association of Wine Economists.
- Jean-Sauveur Ay & Julie Le Gallo, 2021. "The signaling value of nested wine names," Post-Print hal-03268014, HAL.
- Sai Ding & John Knight, 2011.
"Why has China Grown So Fast? The Role of Physical and Human Capital Formation,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(2), pages 141-174, April.
- Sai Ding & John Knight, 2008. "Why has China Grown So Fast? The Role of Physical and Human Capital Formation," Economics Series Working Papers 414, University of Oxford, Department of Economics.
- Rok Spruk & Mitja Kovac, 2018. "Inefficient Growth," Review of Economics and Institutions, Università di Perugia, vol. 9(2).
- Chen, Ruoyu & Jiang, Hanchen & Quintero, Luis E., 2023.
"Measuring the value of rent stabilization and understanding its implications for racial inequality: Evidence from New York City,"
Regional Science and Urban Economics, Elsevier, vol. 103(C).
- Chen, Ruoyu & Jiang, Hanchen & Quintero, Luis E., 2022. "Measuring the Value of Rent Stabilization and Understanding its Implications for Racial Inequality: Evidence from New York City," GLO Discussion Paper Series 1102, Global Labor Organization (GLO).
- R Burger & S du Plessis, 2011.
"Examining the Robustness of Competing Explanations of Slow Growth in African Countries,"
Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 35(3), pages 21-47, December.
- Ronelle Burger, & Stan du Plessis, 2006. "Examining the Robustness of Competing Explanations of Slow Growth in African Countries," Discussion Papers 06/02, University of Nottingham, CREDIT.
- Stan du Plessis & Ronelle Burger, 2006. "Examining the Robustness of Competing Explanations of Slow Growth in African Countries," Working Papers 03/2006, Stellenbosch University, Department of Economics.
- Dangxing Chen & Luyao Zhang, 2023. "Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance," Papers 2301.07060, arXiv.org.
- Ballestar, María Teresa & Mir, Miguel Cuerdo & Pedrera, Luis Miguel Doncel & Sainz, Jorge, 2024. "Effectiveness of tutoring at school: A machine learning evaluation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
- Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001.
"Model uncertainty in cross-country growth regressions,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
- Carmen Fernandez & Eduardo Ley & Mark Steel, 1999. "Model uncertainty in cross-country growth regressions," Econometrics 9903003, University Library of Munich, Germany, revised 06 Oct 2001.
- Carmen Fernandez & Eduardo Ley & Mark Steel, 2001. "Model uncertainty in cross-country growth regressions," Econometrics 0110002, University Library of Munich, Germany.
- Daniel Levy & Tamir Mayer & Alon Raviv, 2020.
"Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers,"
Working Papers
hal-02488796, HAL.
- Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
- Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
- Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
- Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
- Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2022.
"Urban economics in a historical perspective: Recovering data with machine learning,"
Regional Science and Urban Economics, Elsevier, vol. 94(C).
- Gobillon, Laurent & Combes, Pierre-Philippe & Zylberberg, Yanos, 2020. "Urban economics in a historical perspective: Recovering data with machine learning," CEPR Discussion Papers 15308, C.E.P.R. Discussion Papers.
- Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2022. "Urban Economics in a Historical Perspective: Recovering Data with Machine Learning," PSE-Ecole d'économie de Paris (Postprint) halshs-03673240, HAL.
- Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2021. "Urban economics in a historical perspective: Recovering data with machine learning," Working Papers halshs-03231786, HAL.
- Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2022. "Urban Economics in a Historical Perspective: Recovering Data with Machine Learning," Post-Print halshs-03673240, HAL.
- Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2021. "Urban Economics in a Historical Perspective: Recovering Data with Machine Learning," IZA Discussion Papers 14392, Institute of Labor Economics (IZA).
- Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2021. "Urban economics in a historical perspective: Recovering data with machine learning," PSE Working Papers halshs-03231786, HAL.
- Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2022. "Urban Economics in a Historical Perspective: Recovering Data with Machine Learning," SciencePo Working papers Main halshs-03673240, HAL.
- Martin Gassebner & Jerg Gutmann & Stefan Voigt, 2016.
"When to expect a coup d’état? An extreme bounds analysis of coup determinants,"
Public Choice, Springer, vol. 169(3), pages 293-313, December.
- Martin Gassebner & Jerg Gutmann & Stefan Voigt, 2016. "When to expect a coup d’état? An extreme bounds analysis of coup determinants," KOF Working papers 16-409, KOF Swiss Economic Institute, ETH Zurich.
- Gassebner, Martin & Gutmann, Jerg & Voigt, Stefan, 2016. "When to expect a coup d’état? An extreme bounds analysis of coup determinants," ILE Working Paper Series 3, University of Hamburg, Institute of Law and Economics.
- Martin Gassebner & Jerg Gutmann & Stefan Voigt, 2016. "When to Expect a Coup D'État? An Extreme Bounds Analysis of Coup Determinants," CESifo Working Paper Series 6065, CESifo.
- Barzin,Samira & Avner,Paolo & Maruyama Rentschler,Jun Erik & O’Clery,Neave, 2022. "Where Are All the Jobs ? A Machine Learning Approach for High Resolution Urban Employment Prediction inDeveloping Countries," Policy Research Working Paper Series 9979, The World Bank.
- Arenas, Andreu & Calsamiglia, Caterina, 2022.
"Gender Differences in High-Stakes Performance and College Admission Policies,"
IZA Discussion Papers
15550, Institute of Labor Economics (IZA).
- Andreu Arenas & Caterina Calsamiglia, 2023. "Gender Differences in High-Stakes Performance and College Admission Policies," Working Papers 2023/13, Institut d'Economia de Barcelona (IEB).
- Tsang, Andrew, 2021.
"Uncovering Heterogeneous Regional Impacts of Chinese Monetary Policy,"
MPRA Paper
110703, University Library of Munich, Germany.
- Tsang, Andrew, 2021. "Uncovering Heterogeneous Regional Impacts of Chinese Monetary Policy," WiSo-HH Working Paper Series 62, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CWA-2021-03-15 (Central and Western Asia)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:metaar:t93cg. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/metaarxiv .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.