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Merlise A. Clyde

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Daniel Benjamin & James Berger & Magnus Johannesson & Brian Nosek & E. Wagenmakers & Richard Berk & Kenneth Bollen & Bjorn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Christopher Chambe, 2017. "Redefine Statistical Significance," Artefactual Field Experiments 00612, The Field Experiments Website.
    • Daniel J. Benjamin & James O. Berger & Magnus Johannesson & Brian A. Nosek & E.-J. Wagenmakers & Richard Berk & Kenneth A. Bollen & Björn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Chr, 2018. "Redefine statistical significance," Nature Human Behaviour, Nature, vol. 2(1), pages 6-10, January.

    Mentioned in:

    1. [統計][経済][科学]新発見の統計的有意性のp値の閾値は5%から0.5%に下げよ
      by himaginary in himaginaryの日記 on 2017-08-29 05:00:00
    2. New p-Value Thresholds for Statistical Significance
      by Francis Diebold in No Hesitations on 2017-08-28 04:46:00
    3. More on New p-Value Thresholds
      by Francis Diebold in No Hesitations on 2017-09-04 22:17:00

Working papers

  1. Daniel Benjamin & James Berger & Magnus Johannesson & Brian Nosek & E. Wagenmakers & Richard Berk & Kenneth Bollen & Bjorn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Christopher Chambe, 2017. "Redefine Statistical Significance," Artefactual Field Experiments 00612, The Field Experiments Website.
    • Daniel J. Benjamin & James O. Berger & Magnus Johannesson & Brian A. Nosek & E.-J. Wagenmakers & Richard Berk & Kenneth A. Bollen & Björn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Chr, 2018. "Redefine statistical significance," Nature Human Behaviour, Nature, vol. 2(1), pages 6-10, January.

    Cited by:

    1. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    2. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    3. Dreber, Anna & Heikensten, Emma & Säve-Söderbergh, Jenny, 2022. "Why do women ask for less?," Labour Economics, Elsevier, vol. 78(C).
    4. Thomas Buser & Rafael Ahlskog & Magnus Johannesson & Sven Oskarsson, 2022. "Occupational sorting on genes," Tinbergen Institute Discussion Papers 22-062/I, Tinbergen Institute, revised 29 Mar 2023.
    5. Orozco, Valérie & Bontemps, Christophe & Maigné, Elise & Piguet, V. & Hofstetter, A. & Lacroix, Anne & Levert, F. & Rousselle, J.M, 2018. "How To Make A Pie: Reproducible Research for Empirical Economics & Econometrics," TSE Working Papers 18-933, Toulouse School of Economics (TSE).
    6. Gunter, Ulrich & Önder, Irem & Smeral, Egon, 2019. "Scientific value of econometric tourism demand studies," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.
    7. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    8. 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.
    9. Wan, Shuaibin & Liang, Xiongwei & Jiang, Haoran & Sun, Jing & Djilali, Ned & Zhao, Tianshou, 2021. "A coupled machine learning and genetic algorithm approach to the design of porous electrodes for redox flow batteries," Applied Energy, Elsevier, vol. 298(C).
    10. Dudek, Thomas & Brenøe, Anne Ardila & Feld, Jan & Rohrer, Julia, 2022. "No Evidence That Siblings' Gender Affects Personality across Nine Countries," IZA Discussion Papers 15137, Institute of Labor Economics (IZA).
    11. van Hugten, Joeri & Coreynen, Wim & Vanderstraeten, Johanna & van Witteloostuijn, Arjen, 2023. "The Dunning-Kruger effect and entrepreneurial self-efficacy: How tenure and search distance jointly direct entrepreneurial self-efficacy," Journal of Business Research, Elsevier, vol. 161(C).
    12. van de Weijer, Margot P. & de Vries, Lianne P. & Pelt, Dirk H.M. & Ligthart, Lannie & Willemsen, Gonneke & Boomsma, Dorret I. & de Geus, Eco & Bartels, Meike, 2022. "Self-rated health when population health is challenged by the COVID-19 pandemic; a longitudinal study," Social Science & Medicine, Elsevier, vol. 306(C).
    13. Rene Schwaiger & Laura Hueber, 2021. "Do MTurkers Exhibit Myopic Loss Aversion?," Working Papers 2021-12, Faculty of Economics and Statistics, Universität Innsbruck.
    14. Kellner, Ralf & Rösch, Daniel, 2021. "A Bayesian Re-Interpretation of “significant” empirical financial research," Finance Research Letters, Elsevier, vol. 38(C).
    15. Huber, Christoph & Huber, Juergen & Kirchler, Michael, 2021. "Volatility shocks and investment behavior," OSF Preprints jr4eb, Center for Open Science.
    16. John List, 2024. "Optimally Generate Policy-Based Evidence Before Scaling," Natural Field Experiments 00783, The Field Experiments Website.
    17. Luigi Pace & Alessandra Salvan, 2020. "Likelihood, Replicability and Robbins' Confidence Sequences," International Statistical Review, International Statistical Institute, vol. 88(3), pages 599-615, December.
    18. Barrafrem, Kinga & Västfjäll, Daniel & Tinghög, Gustav, 2021. "The arithmetic of outcome editing in financial and social domains," Journal of Economic Psychology, Elsevier, vol. 86(C).
    19. Christoph Huber & Anna Dreber & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Utz Weitzel & Miguel Abellán & Xeniya Adayeva & Fehime Ceren Ay & Kai Barron & Zachariah Berry & Werner Bönte , 2023. "Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(23), pages 2215572120-, June.
    20. Felix Holzmeister & Magnus Johannesson & Robert Böhm & Anna Dreber & Jürgen Huber & Michael Kirchler, 2023. "Heterogeneity in effect size estimates: Empirical evidence and practical implications," Working Papers 2023-17, Faculty of Economics and Statistics, Universität Innsbruck.
    21. Neyse, Levent & Fossen, Frank M. & Johannesson, Magnus & Dreber, Anna, 2023. "Cognitive reflection and 2D:4D: Evidence from a large population sample," Discussion Papers, Research Unit: Market Behavior SP II 2023-201, WZB Berlin Social Science Center.
    22. John K. Kruschke, 2021. "Bayesian Analysis Reporting Guidelines," Nature Human Behaviour, Nature, vol. 5(10), pages 1282-1291, October.
    23. Yannick Hoga, 2022. "Quantifying the data-dredging bias in structural break tests," Statistical Papers, Springer, vol. 63(1), pages 143-155, February.
    24. Ardila Brenoe, Anne & Eyibak, Zeynep & Heursen, Lea & Ranehill, Eva & Weber, Roberto A, 2024. "Gender Identity and Economic Decision Making," Working Papers in Economics 845, University of Gothenburg, Department of Economics.
    25. Colin F. Camerer & Anna Dreber & Felix Holzmeister & Teck-Hua Ho & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Gideon Nave & Brian A. Nosek & Thomas Pfeiffer & Adam Altmejd & Nick Buttrick , 2018. "Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015," Nature Human Behaviour, Nature, vol. 2(9), pages 637-644, September.
    26. Christoph Huber & Jürgen Huber & Michael Kirchler, 2020. "Market shocks and professionals' investment behavior - Evidence from the COVID-19 crash," Working Papers 2020-11, Faculty of Economics and Statistics, Universität Innsbruck.
    27. Frank M. Fossen & Levent Neyse & Magnus Johannesson & Anna Dreber, 2022. "2D:4D and Self-Employment: A Preregistered Replication Study in a Large General Population Sample," Entrepreneurship Theory and Practice, , vol. 46(1), pages 21-43, January.
    28. Thomas Buser & Rafael Ahlskog & Magnus Johannesson & Philipp Koellinger & Sven Oskarsson, 2021. "Using Genes to Explore the Effects of Cognitive and Non-cognitive Skills on Education and Labor Market Outcomes," Tinbergen Institute Discussion Papers 21-088/I, Tinbergen Institute, revised 29 Mar 2023.
    29. Arnold, Gwen & Farrer, Benjamin & Holahan, Robert, 2018. "How do landowners learn about high-volume hydraulic fracturing? A survey of Eastern Ohio landowners in active or proposed drilling units," Energy Policy, Elsevier, vol. 114(C), pages 455-464.
    30. Gemma T. Wallace & Karen C. Barrett & Kimberly L. Henry & Mark A. Prince & Bradley T. Conner, 2023. "Examining underlying structures of cognitive emotion regulation strategies using exploratory structural equation modeling," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4171-4192, October.
    31. Thomas Buser, 2024. "Adversarial economic preferences predict right-wing voting," Tinbergen Institute Discussion Papers 24-001/I, Tinbergen Institute.
    32. Armando Holzknecht & Jürgen Huber & Michael Kirchler & Tibor Neugebauer, 2024. "Speculating in zero-value assets: The greater fool game experiment," Working Papers 2024-09, Faculty of Economics and Statistics, Universität Innsbruck.
    33. Dreyfuss, Bnaya & Heffetz, Ori & Hoffman, Guy & Ishai, Guy & Kshirsagar, Alap, 2024. "Additive vs. subtractive earning in shared human-robot work environments," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 692-704.
    34. Jim A. C. Everett & Clara Colombatto & Edmond Awad & Paulo Boggio & Björn Bos & William J. Brady & Megha Chawla & Vladimir Chituc & Dongil Chung & Moritz A. Drupp & Srishti Goel & Brit Grosskopf & Fre, 2021. "Moral dilemmas and trust in leaders during a global health crisis," Nature Human Behaviour, Nature, vol. 5(8), pages 1074-1088, August.
    35. Logg, Jennifer M. & Dorison, Charles A., 2021. "Pre-registration: Weighing costs and benefits for researchers," Organizational Behavior and Human Decision Processes, Elsevier, vol. 167(C), pages 18-27.
    36. Dreber, Anna & Johannesson, Magnus & Yang, Yifan, 2023. "Selective Reporting of Placebo Tests in Top Economics Journals," I4R Discussion Paper Series 31, The Institute for Replication (I4R).
    37. Paul Heaton & Caleb Flint, 2021. "Medicaid coverage expansions and liability insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 29-51, March.
    38. Lutz Bornmann & Julian N. Marewski, 2024. "Opium in science and society: numbers and other quantifications," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5313-5346, September.
    39. Elbæk, Christian T. & Lystbæk, Martin Nørhede & Mitkidis, Panagiotis, 2022. "On the psychology of bonuses: The effects of loss aversion and Yerkes-Dodson law on performance in cognitively and mechanically demanding tasks," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    40. Mohamed Gaber & Edward J. Lusk, 2019. "A Vetting Protocol for the Analytical Procedures Platform for the AP-Phase of PCAOB Audits," Accounting and Finance Research, Sciedu Press, vol. 8(4), pages 1-43, November.
    41. Erik W. van Zwet & Eric A. Cator, 2021. "The significance filter, the winner's curse and the need to shrink," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(4), pages 437-452, November.
    42. Rose, Julia & Kirchler, Michael & Palan, Stefan, 2023. "Status and reputation nudging," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 105(C).
    43. David Bilén & Anna Dreber & Magnus Johannesson, 2021. "Are women more generous than men? A meta-analysis," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 7(1), pages 1-18, September.
    44. Beau Coker & Cynthia Rudin & Gary King, 2021. "A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results," Management Science, INFORMS, vol. 67(10), pages 6174-6197, October.
    45. Kseniia Zahrai & Ekant Veer & Paul William Ballantine & Huibert Peter de Vries & Girish Prayag, 2022. "Either you control social media or social media controls you: Understanding the impact of self‐control on excessive social media use from the dual‐system perspective," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(2), pages 806-848, June.
    46. Rinne, Sonja, 2024. "Estimating the merit-order effect using coarsened exact matching: Reconciling theory with the empirical results to improve policy implications," Energy Policy, Elsevier, vol. 185(C).
    47. Kim, Jae H. & Shamsuddin, Abul, 2023. "Stock market anomalies: An extreme bounds analysis," International Review of Financial Analysis, Elsevier, vol. 90(C).
    48. Sarstedt, Marko & Adler, Susanne J., 2023. "An advanced method to streamline p-hacking," Journal of Business Research, Elsevier, vol. 163(C).
    49. Heggedal, Tom-Reiel & Helland, Leif & Våge Knutsen, Magnus, 2022. "The power of outside options in the presence of obstinate types," Games and Economic Behavior, Elsevier, vol. 136(C), pages 454-468.
    50. Lucio De Capitani & Daniele De Martini, 2021. "Improving reproducibility probability estimation and preserving RP-testing," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 49-77, March.
    51. Schwaiger, Rene & Kirchler, Michael & Lindner, Florian & Weitzel, Utz, 2020. "Determinants of investor expectations and satisfaction. A study with financial professionals," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    52. Kelter, Riko, 2022. "Power analysis and type I and type II error rates of Bayesian nonparametric two-sample tests for location-shifts based on the Bayes factor under Cauchy priors," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
    53. Abel Rodríguez & Bruno Sansó, 2023. "An interview with Luis Raúl Pericchi," International Statistical Review, International Statistical Institute, vol. 91(1), pages 1-17, April.
    54. Williams, Cole Randall, 2019. "How redefining statistical significance can worsen the replication crisis," Economics Letters, Elsevier, vol. 181(C), pages 65-69.
    55. Adler, Susanne Jana & Röseler, Lukas & Schöniger, Martina Katharina, 2023. "A toolbox to evaluate the trustworthiness of published findings," Journal of Business Research, Elsevier, vol. 167(C).
    56. Hensel, Lukas & Witte, Marc & Caria, A. Stefano & Fetzer, Thiemo & Fiorin, Stefano & Götz, Friedrich M. & Gomez, Margarita & Haushofer, Johannes & Ivchenko, Andriy & Kraft-Todd, Gordon & Reutskaja, El, 2022. "Global Behaviors, Perceptions, and the Emergence of Social Norms at the Onset of the COVID-19 Pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 473-496.
    57. Oluleye, Gbemi & Gandiglio, Marta & Santarelli, Massimo & Hawkes, Adam, 2021. "Pathways to commercialisation of biogas fuelled solid oxide fuel cells in European wastewater treatment plants," Applied Energy, Elsevier, vol. 282(PA).
    58. Paul Adams & Benedict Guttman‐Kenney & Lucy Hayes & Stefan Hunt & David Laibson & Neil Stewart, 2022. "Do Nudges Reduce Borrowing and Consumer Confusion in the Credit Card Market?," Economica, London School of Economics and Political Science, vol. 89(S1), pages 178-199, June.
    59. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    60. Wickes, Ron, 2021. "Trade deficits and trade conflict: The United States and Japan," Japan and the World Economy, Elsevier, vol. 60(C).
    61. Ron Berman & Christophe Van den Bulte, 2022. "False Discovery in A/B Testing," Management Science, INFORMS, vol. 68(9), pages 6762-6782, September.
    62. Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
    63. Sadri, Arash, 2022. "The Ultimate Cause of the “Reproducibility Crisis”: Reductionist Statistics," MetaArXiv yxba5, Center for Open Science.
    64. Schaerer, Michael & du Plessis, Christilene & Nguyen, My Hoang Bao & van Aert, Robbie C.M. & Tiokhin, Leo & Lakens, Daniël & Giulia Clemente, Elena & Pfeiffer, Thomas & Dreber, Anna & Johannesson, Mag, 2023. "On the trajectory of discrimination: A meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 179(C).
    65. Holzmeister, Felix & Huber, Jürgen & Kirchler, Michael & Schwaiger, Rene, 2022. "Nudging debtors to pay their debt: Two randomized controlled trials," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 535-551.
    66. Finley, Brian & Kalwij, Adriaan & Kapteyn, Arie, 2022. "Born to be wild: Second-to-fourth digit length ratio and risk preferences," Economics & Human Biology, Elsevier, vol. 47(C).
    67. Aris Spanos, 2022. "Frequentist Model-based Statistical Induction and the Replication Crisis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 133-159, September.
    68. Christoph Semken & David Rossell, 2022. "Specification analysis for technology use and teenager well‐being: Statistical validity and a Bayesian proposal," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1330-1355, November.
    69. Granberg, Mark & Andersson, Per A. & Ahmed, Ali, 2020. "Hiring Discrimination Against Transgender People: Evidence from a Field Experiment," Labour Economics, Elsevier, vol. 65(C).
    70. Surucu-Balci, Ebru & Iris, Çağatay & Balci, Gökcay, 2024. "Digital information in maritime supply chains with blockchain and cloud platforms: Supply chain capabilities, barriers, and research opportunities," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    71. Johnstone, David, 2022. "Accounting research and the significance test crisis," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 89(C).
    72. Bickel, David R., 2020. "Departing from Bayesian inference toward minimaxity to the extent that the posterior distribution is unreliable," Statistics & Probability Letters, Elsevier, vol. 164(C).
    73. Kline, Brendan, 2024. "Classical p-values and the Bayesian posterior probability that the hypothesis is approximately true," Journal of Econometrics, Elsevier, vol. 240(1).
    74. Schwaiger, Rene & Hueber, Laura, 2021. "Do MTurkers exhibit myopic loss aversion?," Economics Letters, Elsevier, vol. 209(C).
    75. Baltussen, Guido & Swinkels, Laurens & Van Vliet, Pim, 2021. "Global factor premiums," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1128-1154.
    76. Sebastian Bachler & Armando Holzknecht & Jürgen Huber & Michael Kirchler, 2024. "From Individual Choices to the 4-Eyes-Principle: The Big Robber Game revisited among Financial Professionals and Students," Working Papers 2024-04, Faculty of Economics and Statistics, Universität Innsbruck.
    77. Kalwij, Adriaan, 2023. "Risk preferences, preventive behaviour, and the probability of a loss: Empirical evidence from the COVID-19 pandemic," Social Science & Medicine, Elsevier, vol. 334(C).
    78. Latan, Hengky & Lopes de Sousa Jabbour, Ana Beatriz & Sarkis, Joseph & Chiappetta Jabbour, Charbel Jose & Ali, Murad, 2024. "The nexus of supply chain performance and blockchain technology in the digitalization era: Insights from a fast-growing economy," Journal of Business Research, Elsevier, vol. 172(C).
    79. Tom Engsted, 2024. "What Is the False Discovery Rate in Empirical Research?," Econ Journal Watch, Econ Journal Watch, vol. 21(1), pages 1-92–112, March.

Articles

  1. Merlise A. Clyde & Joyee Ghosh, 2012. "Finite population estimators in stochastic search variable selection," Biometrika, Biometrika Trust, vol. 99(4), pages 981-988.

    Cited by:

    1. Alfredo Altuzarra & Pilar Gargallo & José María Moreno-Jiménez & Manuel Salvador, 2022. "Identification of Homogeneous Groups of Actors in a Local AHP-Multiactor Context with a High Number of Decision-Makers: A Bayesian Stochastic Search," Mathematics, MDPI, vol. 10(3), pages 1-20, February.
    2. Liquet, Benoît & Bottolo, Leonardo & Campanella, Gianluca & Richardson, Sylvia & Chadeau-Hyam, Marc, 2016. "R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i02).

  2. Ghosh, Joyee & Clyde, Merlise A., 2011. "Rao–Blackwellization for Bayesian Variable Selection and Model Averaging in Linear and Binary Regression: A Novel Data Augmentation Approach," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 1041-1052.

    Cited by:

    1. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    2. Gonzalo García‐Donato & Stefano Cabras & María Eugenia Castellanos, 2023. "Model uncertainty quantification in Cox regression," Biometrics, The International Biometric Society, vol. 79(3), pages 1726-1736, September.
    3. Joyee Ghosh & Andrew E. Ghattas, 2015. "Bayesian Variable Selection Under Collinearity," The American Statistician, Taylor & Francis Journals, vol. 69(3), pages 165-173, August.
    4. Chris J. Oates & Mark Girolami & Nicolas Chopin, 2017. "Control functionals for Monte Carlo integration," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 695-718, June.
    5. Perrakis, Konstantinos & Ntzoufras, Ioannis & Tsionas, Efthymios G., 2014. "On the use of marginal posteriors in marginal likelihood estimation via importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 54-69.
    6. Li Ma, 2015. "Scalable Bayesian Model Averaging Through Local Information Propagation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 795-809, June.

  3. Liang, Feng & Paulo, Rui & Molina, German & Clyde, Merlise A. & Berger, Jim O., 2008. "Mixtures of g Priors for Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 410-423, March.

    Cited by:

    1. Björn R H Blomqvist & Richard P Mann & David J T Sumpter, 2018. "Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-23, May.
    2. Camarero, Mariam & Forte, Anabel & Garcia-Donato, Gonzalo & Mendoza, Yurena & Ordoñez, Javier, 2015. "Variable selection in the analysis of energy consumption–growth nexus," Energy Economics, Elsevier, vol. 52(PA), pages 207-216.
    3. Minerva Mukhopadhyay & Tapas Samanta, 2017. "A mixture of g-priors for variable selection when the number of regressors grows with the sample size," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 377-404, June.
    4. Jose Olmo & Marcos Sanso‐Navarro, 2021. "Modeling the spread of COVID‐19 in New York City," Papers in Regional Science, Wiley Blackwell, vol. 100(5), pages 1209-1229, October.
    5. Reichlin, Lucrezia & Giannone, Domenico & Lenza, Michele, 2010. "Market freedom and the global recession," CEPR Discussion Papers 7884, C.E.P.R. Discussion Papers.
    6. Kupiec, Paul H., 2020. "Policy uncertainty and bank stress testing," Journal of Financial Stability, Elsevier, vol. 51(C).
    7. M. J. Bayarri & G. García‐Donato, 2008. "Generalization of Jeffreys divergence‐based priors for Bayesian hypothesis testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 981-1003, November.
    8. Iftekhar Hasan & Roman Horvath & Jan Mares, 2018. "Finance and Wealth Inequality," Working Papers IES 2018/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2018.
    9. Robert Kohn & Rachida Ouysse, 2007. "Bayesian Variable Selection of Risk Factors in the APT Model," Discussion Papers 2007-32, School of Economics, The University of New South Wales.
    10. Enrico Petretto & Leonardo Bottolo & Sarah R Langley & Matthias Heinig & Chris McDermott-Roe & Rizwan Sarwar & Michal Pravenec & Norbert Hübner & Timothy J Aitman & Stuart A Cook & Sylvia Richardson, 2010. "New Insights into the Genetic Control of Gene Expression using a Bayesian Multi-tissue Approach," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-13, April.
    11. Rios, Vicente, 2019. "New Evidence on the Size and Drivers of the Shadow Economy in Spain: A Model Averaging Approach," MPRA Paper 97504, University Library of Munich, Germany.
    12. Njindan Iyke, Bernard, 2015. "Macro Determinants of the Real Exchange Rate in a Small Open Small Island Economy: Evidence from Mauritius via BMA," MPRA Paper 68968, University Library of Munich, Germany.
    13. Gelman Andrew & Robert Christian P. & Rousseau Judith, 2013. "Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin," Statistics & Risk Modeling, De Gruyter, vol. 30(2), pages 105-120, June.
    14. Sousa, João & Sousa, Ricardo M., 2013. "Asset returns under model uncertainty: evidence from the euro area, the U.S. and the U.K," Working Paper Series 1575, European Central Bank.
    15. Yen-Shiu Chin & Ting-Li Chen, 2016. "Minimizing variable selection criteria by Markov chain Monte Carlo," Computational Statistics, Springer, vol. 31(4), pages 1263-1286, December.
    16. Temple, Jonathan & Rockey, James, 2015. "Growth Econometrics for Agnostics and True Believers," CEPR Discussion Papers 10590, C.E.P.R. Discussion Papers.
    17. Min Wang & Xiaoqian Sun & Tao Lu, 2015. "Bayesian structured variable selection in linear regression models," Computational Statistics, Springer, vol. 30(1), pages 205-229, March.
    18. Eduardo Ley & Mark F.J. Steel, 2009. "On the effect of prior assumptions in Bayesian model averaging with applications to growth regression This article was published online on 30 March 2009. An error was subsequently identified. This not," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 651-674.
    19. Christian P. Robert, 2013. "On the jeffreys-Lindley's Paradox," Working Papers 2013-46, Center for Research in Economics and Statistics.
    20. Branimir Jovanovic, 2012. "How Policy Actions Affect Short-term Post-crisis Recovery?," CEIS Research Paper 253, Tor Vergata University, CEIS, revised 05 Oct 2012.
    21. David Kaplan, 2021. "On the Quantification of Model Uncertainty: A Bayesian Perspective," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 215-238, March.
    22. Endrész, Marianna & Skudelny, Frauke, 2016. "Crisis severity and the international trade network," Working Paper Series 1971, European Central Bank.
    23. Dimitris Fouskakis & Ioannis Ntzoufras, 2017. "Information consistency of the Jeffreys power-expected-posterior prior in Gaussian linear models," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 371-380, December.
    24. Alfredo Altuzarra & Pilar Gargallo & José María Moreno-Jiménez & Manuel Salvador, 2022. "Identification of Homogeneous Groups of Actors in a Local AHP-Multiactor Context with a High Number of Decision-Makers: A Bayesian Stochastic Search," Mathematics, MDPI, vol. 10(3), pages 1-20, February.
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    160. Dimitris Fouskakis & Ioannis Ntzoufras, 2020. "Bayesian Model Averaging Using Power-Expected-Posterior Priors," Econometrics, MDPI, vol. 8(2), pages 1-15, May.
    161. Han, Ningren & Ram, Rajeev J., 2020. "Bayesian modeling and computation for analyte quantification in complex mixtures using Raman spectroscopy," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
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    163. Min Wang & Guangying Liu, 2016. "A Simple Two-Sample Bayesian t -Test for Hypothesis Testing," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 195-201, May.
    164. Mai Dao & Min Wang & Souparno Ghosh & Keying Ye, 2022. "Bayesian variable selection and estimation in quantile regression using a quantile-specific prior," Computational Statistics, Springer, vol. 37(3), pages 1339-1368, July.
    165. Varriale, Vincenzo & De Pascalis, Vilfredo & van der Molen, Maurits W., 2021. "Post-error slowing is associated with intelligence," Intelligence, Elsevier, vol. 89(C).
    166. Arnab Kumar Maity & Sanjib Basu & Santu Ghosh, 2021. "Bayesian criterion‐based variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 835-857, August.
    167. Yixin Fang & Heng Lian & Hua Liang, 2018. "A generalized partially linear framework for variance functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1147-1175, October.
    168. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model," Working Papers 2007, Department of Applied Economics II, Universidad de Valencia.
    169. Xiaoquan Wen, 2017. "Robust Bayesian FDR Control Using Bayes Factors, with Applications to Multi-tissue eQTL Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 28-49, June.
    170. David Coyne & Chih Ming Tan, 2012. "Do Political Institutions Yield Multiple Growth Regimes?," Working Paper series 36_12, Rimini Centre for Economic Analysis.
    171. Scott D. Goddard & Valen E. Johnson, 2016. "Restricted most powerful Bayesian tests for linear models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1162-1177, December.
    172. Shahram Amini & Christopher F. Parmeter, 2020. "A Review of the ‘BMS’ Package for R with Focus on Jointness," Econometrics, MDPI, vol. 8(1), pages 1-21, February.
    173. Karol Szafranek & Marek Kwas & Grzegorz Szafrański & Zuzanna Wośko, 2020. "Common Determinants of Credit Default Swap Premia in the North American Oil and Gas Industry. A Panel BMA Approach," Energies, MDPI, vol. 13(23), pages 1-23, November.
    174. Bodganand, Dima & Canepa, Alessandra, 2024. "Environmental Performance and Institutions Quality in Europe: A Bayesian Model Averaging Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202421, University of Turin.
    175. Malesios, C & Demiris, N & Kalogeropoulos, K & Ntzoufras, I, 2017. "Bayesian epidemic models for spatially aggregated count data," LSE Research Online Documents on Economics 77939, London School of Economics and Political Science, LSE Library.
    176. Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
    177. Jeong, Seonghyun & Park, Minjae & Park, Taeyoung, 2017. "Analysis of binary longitudinal data with time-varying effects," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 145-153.
    178. Uddin, Md Nazir & Gaskins, Jeremy T., 2023. "Shared Bayesian variable shrinkage in multinomial logistic regression," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    179. Yu, Chi Wai & Clarke, Bertrand, 2010. "Asymptotics of Bayesian median loss estimation," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 1950-1958, October.
    180. Yu-Fang Chien & Haiming Zhou & Timothy Hanson & Theodore Lystig, 2023. "Informative g -Priors for Mixed Models," Stats, MDPI, vol. 6(1), pages 1-23, January.
    181. Kwon, Deukwoo & Landi, Maria Teresa & Vannucci, Marina & Issaq, Haleem J. & Prieto, DaRue & Pfeiffer, Ruth M., 2011. "An efficient stochastic search for Bayesian variable selection with high-dimensional correlated predictors," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2807-2818, October.
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    183. Paola Berchialla & Veronica Sciannameo & Sara Urru & Corrado Lanera & Danila Azzolina & Dario Gregori & Ileana Baldi, 2021. "Adjustment for Baseline Covariates to Increase Efficiency in RCTs with Binary Endpoint: A Comparison of Bayesian and Frequentist Approaches," IJERPH, MDPI, vol. 18(15), pages 1-9, July.
    184. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
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    187. Malefaki, Valia, 2015. "On Flexible Linear Factor Stochastic Volatility Models," MPRA Paper 62216, University Library of Munich, Germany.
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  4. Francesca Dominici & Lianne Sheppard & Merlise Clyde, 2003. "Health Effects of Air Pollution: A Statistical Review," International Statistical Review, International Statistical Institute, vol. 71(2), pages 243-276, August.

    Cited by:

    1. X. Pautrel, 2008. "Reconsidering the Impact of the Environment on Long-run Growth when Pollution Influences Health and Agents have a Finite-lifetime," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 40(1), pages 37-52, May.
    2. Chen, Xie & Mao, Hongzhi & Cheng, Nan & Ma, Ling & Tian, Zhiyong & Luo, Yongqiang & Zhou, Chaohui & Li, Huai & Wang, Qian & Kong, Weiqiang & Fan, Jianhua, 2024. "Climate change impacts on global photovoltaic variability," Applied Energy, Elsevier, vol. 374(C).
    3. Winifred U. Anake & Faith O. Bayode & Hassana O. Jonathan & Conrad A. Omonhinmin & Oluwole A. Odetunmibi & Timothy A. Anake, 2022. "Screening of Plant Species Response and Performance for Green Belt Development: Implications for Semi-Urban Ecosystem Restoration," Sustainability, MDPI, vol. 14(7), pages 1-14, March.
    4. Julie E. Goodman & Catherine Petito Boyce & Sonja N. Sax & Leslie A. Beyer & Robyn L. Prueitt, 2015. "Rethinking Meta‐Analysis: Applications for Air Pollution Data and Beyond," Risk Analysis, John Wiley & Sons, vol. 35(6), pages 1017-1039, June.
    5. Sabel, Clive Eric & Wilson, Jeff Gaines & Kingham, Simon & Tisch, Catherine & Epton, Mike, 2007. "Spatial implications of covariate adjustment on patterns of risk: Respiratory hospital admissions in Christchurch, New Zealand," Social Science & Medicine, Elsevier, vol. 65(1), pages 43-59, July.
    6. Phuong T. Vu & Timothy V. Larson & Adam A. Szpiro, 2020. "Probabilistic predictive principal component analysis for spatially misaligned and high‐dimensional air pollution data with missing observations," Environmetrics, John Wiley & Sons, Ltd., vol. 31(4), June.
    7. Peter Guttorp, 2003. "Environmental Statistics—A Personal View," International Statistical Review, International Statistical Institute, vol. 71(2), pages 169-179, August.
    8. Adam A. Szpiro & Lianne Sheppard & Sara D. Adar & Joel D. Kaufman, 2014. "Estimating acute air pollution health effects from cohort study data," Biometrics, The International Biometric Society, vol. 70(1), pages 164-174, March.
    9. Magali Delmas & Maria Montes-Sancho & Jay P. Shimshack, 2007. "Information Disclosure Policies: Evidence from the Electricity Industry," Discussion Papers Series, Department of Economics, Tufts University 0707, Department of Economics, Tufts University.
    10. Ruth M. Pfeiffer & Mitchell H. Gail, 2023. "Discussion of “A formal causal interpretation of the case‐crossover design” by Zach Shahn, Miguel A. Hernan, and James M. Robins," Biometrics, The International Biometric Society, vol. 79(2), pages 1346-1348, June.
    11. Beatty, Timothy K.M. & Shimshack, Jay P., 2014. "Air pollution and children's respiratory health: A cohort analysis," Journal of Environmental Economics and Management, Elsevier, vol. 67(1), pages 39-57.
    12. Stefka Fidanova & Petar Zhivkov & Olympia Roeva, 2022. "InterCriteria Analysis Applied on Air Pollution Influence on Morbidity," Mathematics, MDPI, vol. 10(7), pages 1-8, April.
    13. Phuong T. Vu & Adam A. Szpiro & Noah Simon, 2022. "Spatial matrix completion for spatially misaligned and high‐dimensional air pollution data," Environmetrics, John Wiley & Sons, Ltd., vol. 33(4), June.
    14. Qinling Yan & Sanyi Tang & Zhen Jin & Yanni Xiao, 2019. "Identifying Risk Factors Of A(H7N9) Outbreak by Wavelet Analysis and Generalized Estimating Equation," IJERPH, MDPI, vol. 16(8), pages 1-13, April.
    15. Severine Deguen & Nina Ahlers & Morgane Gilles & Arlette Danzon & Marion Carayol & Denis Zmirou-Navier & Wahida Kihal-Talantikite, 2018. "Using a Clustering Approach to Investigate Socio-Environmental Inequality in Preterm Birth—A Study Conducted at Fine Spatial Scale in Paris (France)," IJERPH, MDPI, vol. 15(9), pages 1-19, August.

  5. Merlise Clyde & Edward I. George, 2000. "Flexible empirical Bayes estimation for wavelets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 681-698.

    Cited by:

    1. Reményi, Norbert & Vidakovic, Brani, 2013. "Λ-neighborhood wavelet shrinkage," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 404-416.
    2. Peter Müeller & Fernando A. Quintana & Garritt Page, 2018. "Nonparametric Bayesian inference in applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 175-206, June.
    3. Abramovich, Felix & Besbeas, Panagiotis & Sapatinas, Theofanis, 2002. "Empirical Bayes approach to block wavelet function estimation," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 435-451, June.
    4. Sonia Petrone & Stefano Rizzelli & Judith Rousseau & Catia Scricciolo, 2014. "Empirical Bayes methods in classical and Bayesian inference," METRON, Springer;Sapienza Università di Roma, vol. 72(2), pages 201-215, August.
    5. Nilotpal Sanyal & Marco A. R. Ferreira, 2017. "Bayesian Wavelet Analysis Using Nonlocal Priors with an Application to fMRI Analysis," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(2), pages 361-388, November.
    6. Meiri, Ronen & Zahavi, Jacob, 2006. "Using simulated annealing to optimize the feature selection problem in marketing applications," European Journal of Operational Research, Elsevier, vol. 171(3), pages 842-858, June.
    7. Wang, Y. & Daniels, M.J., 2013. "Bayesian modeling of the dependence in longitudinal data via partial autocorrelations and marginal variances," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 130-140.
    8. Stuart Barber & Guy P. Nason, 2004. "Real nonparametric regression using complex wavelets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 927-939, November.
    9. Hans, Christopher M. & Peruggia, Mario & Wang, Junyan, 2023. "Empirical Bayes Model Averaging with Influential Observations: Tuning Zellner’s g Prior for Predictive Robustness," Econometrics and Statistics, Elsevier, vol. 27(C), pages 102-119.
    10. Stuart Barber & Guy P. Nason & Bernard W. Silverman, 2002. "Posterior probability intervals for wavelet thresholding," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 189-205, May.
    11. Gabriel Huerta, 2005. "Multivariate Bayes Wavelet shrinkage and applications," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(5), pages 529-542.
    12. P. J. Brown & M. Vannucci & T. Fearn, 2002. "Bayes model averaging with selection of regressors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 519-536, August.
    13. Joyee Ghosh & Amy H. Herring & Anna Maria Siega-Riz, 2011. "Bayesian Variable Selection for Latent Class Models," Biometrics, The International Biometric Society, vol. 67(3), pages 917-925, September.
    14. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    15. Andrew Gelman, 2003. "A Bayesian Formulation of Exploratory Data Analysis and Goodness‐of‐fit Testing," International Statistical Review, International Statistical Institute, vol. 71(2), pages 369-382, August.

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