SMART-EXAM: Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Brian J. Gaines & James H. Kuklinski, 2011. "Experimental Estimation of Heterogeneous Treatment Effects Related to Self‐Selection," American Journal of Political Science, John Wiley & Sons, vol. 55(3), pages 724-736, July.
- Bibhas Chakraborty & Eric B. Laber & Yingqi Zhao, 2013. "Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m-Out-of-n Bootstrap Scheme," Biometrics, The International Biometric Society, vol. 69(3), pages 714-723, September.
- Lu Wang & Andrea Rotnitzky & Xihong Lin & Randall E. Millikan & Peter F. Thall, 2012. "Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 493-508, June.
- Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021.
"Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence,"
The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," IZA Discussion Papers 12039, Institute of Labor Economics (IZA).
- Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Papers 1810.13237, arXiv.org, revised Dec 2018.
- Lechner, Michael & Knaus, Michael C. & Strittmatter, Anthony, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," CEPR Discussion Papers 13402, C.E.P.R. Discussion Papers.
- Knaus, Michael C. & Lechner, Michael & anthony.strittmatter@unisg.ch, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Economics Working Paper Series 1817, University of St. Gallen, School of Economics and Political Science.
- Liwen Wu & Junyao Wang & Abdus S. Wahed, 2023. "Interim monitoring in sequential multiple assignment randomized trials," Biometrics, The International Biometric Society, vol. 79(1), pages 368-380, March.
- Dean Knox & Teppei Yamamoto & Matthew A. Baum & Adam J. Berinsky, 2019. "Design, Identification, and Sensitivity Analysis for Patient Preference Trials," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(528), pages 1532-1546, October.
- Ying Kuen Cheung & Bibhas Chakraborty & Karina W. Davidson, 2015. "Sequential multiple assignment randomized trial (SMART) with adaptive randomization for quality improvement in depression treatment program," Biometrics, The International Biometric Society, vol. 71(2), pages 450-459, June.
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.- Michael P. Wallace & Erica E. M. Moodie, 2015. "Doubly‐robust dynamic treatment regimen estimation via weighted least squares," Biometrics, The International Biometric Society, vol. 71(3), pages 636-644, September.
- Yebin Tao & Lu Wang, 2017. "Adaptive contrast weighted learning for multi-stage multi-treatment decision-making," Biometrics, The International Biometric Society, vol. 73(1), pages 145-155, March.
- Q. Clairon & R. Henderson & N. J. Young & E. D. Wilson & C. J. Taylor, 2021. "Adaptive treatment and robust control," Biometrics, The International Biometric Society, vol. 77(1), pages 223-236, March.
- Early Kirstin & Mankoff Jennifer & Fienberg Stephen E., 2017. "Dynamic Question Ordering in Online Surveys," Journal of Official Statistics, Sciendo, vol. 33(3), pages 625-657, September.
- Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
- Engberg, Erik & Görg, Holger & Lodefalk, Magnus & Javed, Farrukh & Längkvist, Martin & Monteiro, Natália & Kyvik Nordås, Hildegunn & Pulito, Giuseppe & Schroeder, Sarah & Tang, Aili, 2023.
"AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries,"
Ratio Working Papers
370, The Ratio Institute.
- Engberg, Erik & Görg, Holger & Lodefalk, Magnus & Javed, Farrukh & Längkvist, Martin & Monteiro, Natália Pimenta & Kyvik Nordås, Hildegunn & Schroeder, Sarah & Tang, Aili, 2024. "AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries," IZA Discussion Papers 16717, Institute of Labor Economics (IZA).
- Erik Engberg & Holger Görg & Magnus Lodefalk & Farrukh Javed & Martin Längkvist & Natália Monteiro & Hildegunn Kyvik Nordås & Giuseppe Pulito & Sarah Schroeder & Aili Tang, 2023. "AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries," NIPE Working Papers 14/2023, NIPE - Universidade do Minho.
- Erik Engberg & Holger Gorg & Magnus Lodefalk & Farrukh Javed & Martin Langkvist & Natalia Monteiro & Hildegunn Nordas & Giuseppe Pulito & Sarah Schroeder & Aili Tang, 2024. "AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries," RF Berlin - CReAM Discussion Paper Series 2414, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
- Engberg, Erik & Görg, Holger & Lodefalk, Magnus & Javed, Farrukh & Längkvist, Martin & Monteiro, Natália & Kyvik Nordås, Hildegunn & Pulito, Giuseppe & Schroeder, Sarah & Tang, Aili, 2023. "AI Unboxed and Jobs: A Novel Measure and Firm-Level Evidence from Three Countries," Working Papers 2023:13, Örebro University, School of Business.
- Pons Rotger, Gabriel & Rosholm, Michael, 2020. "The Role of Beliefs in Long Sickness Absence: Experimental Evidence from a Psychological Intervention," IZA Discussion Papers 13582, Institute of Labor Economics (IZA).
- Daniel Goller, 2023.
"Analysing a built-in advantage in asymmetric darts contests using causal machine learning,"
Annals of Operations Research, Springer, vol. 325(1), pages 649-679, June.
- Goller, Daniel, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Economics Working Paper Series 2013, University of St. Gallen, School of Economics and Political Science.
- Daniel Goller, 2020. "Analysing a built-in advantage in asymmetric darts contests using causal machine learning," Papers 2008.07165, arXiv.org.
- Yiyi Huo & Yingying Fan & Fang Han, 2023. "On the adaptation of causal forests to manifold data," Papers 2311.16486, arXiv.org, revised Dec 2023.
- Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
- Zeyu Bian & Erica E. M. Moodie & Susan M. Shortreed & Sahir Bhatnagar, 2023. "Variable selection in regression‐based estimation of dynamic treatment regimes," Biometrics, The International Biometric Society, vol. 79(2), pages 988-999, June.
- Thomas A. Murray & Peter F. Thall & Ying Yuan & Sarah McAvoy & Daniel R. Gomez, 2017. "Robust Treatment Comparison Based on Utilities of Semi-Competing Risks in Non-Small-Cell Lung Cancer," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 11-23, January.
- Markus Frölich & Martin Huber, 2014.
"Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1697-1711, December.
- Frölich, Markus & Huber, Martin, 2014. "Treatment evaluation with multiple outcome periods under endogeneity and attrition," Economics Working Paper Series 1404, University of St. Gallen, School of Economics and Political Science.
- Frölich, Markus & Huber, Martin, 2014. "Treatment Evaluation with Multiple Outcome Periods under Endogeneity and Attrition," IZA Discussion Papers 7972, Institute of Labor Economics (IZA).
- Ogundari, Kolawole, 2021. "A systematic review of statistical methods for estimating an education production function," MPRA Paper 105283, University Library of Munich, Germany.
- Michael C Knaus, 2022.
"Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation],"
The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
- Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
- Knaus, Michael C., 2020. "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers 13051, Institute of Labor Economics (IZA).
- Michael C. Knaus, 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Papers 2003.03191, arXiv.org, revised Jun 2022.
- Denis Fougère & Nicolas Jacquemet, 2020.
"Policy Evaluation Using Causal Inference Methods,"
SciencePo Working papers Main
hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," PSE-Ecole d'économie de Paris (Postprint) hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Working Papers hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Post-Print hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03098058, HAL.
- Fougère, Denis & Jacquemet, Nicolas, 2020. "Policy Evaluation Using Causal Inference Methods," IZA Discussion Papers 12922, Institute of Labor Economics (IZA).
- Humphreys, Macartan & Scacco, Alexandra, 2020. "The aggregation challenge," World Development, Elsevier, vol. 127(C).
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2023.
"Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium,"
Labour Economics, Elsevier, vol. 80(C).
- Bart Cockx & Michael Lechner & Joost Bollens, 2019. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Papers 1912.12864, arXiv.org, revised Dec 2022.
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," ROA Research Memorandum 006, Maastricht University, Research Centre for Education and the Labour Market (ROA).
- Bart Cockx & Michael Lechner & Joost Bollens, 2020. "Priority of Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium," CESifo Working Paper Series 8297, CESifo.
- Lechner, Michael & Cockx, Bart & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," CEPR Discussion Papers 14270, C.E.P.R. Discussion Papers.
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Economics Working Paper Series 2001, University of St. Gallen, School of Economics and Political Science.
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Research Memorandum 015, Maastricht University, Graduate School of Business and Economics (GSBE).
- Cockx, Bart & Lechner, Michael & Bollens, Joost, 2019. "Priority to Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium," IZA Discussion Papers 12875, Institute of Labor Economics (IZA).
- Bart Cockx & Michael Lechner & Joost Bollens, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/998, Ghent University, Faculty of Economics and Business Administration.
- Bart Cockx & Michael Lechner & Joost Bollens, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," LIDAM Discussion Papers IRES 2020016, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- Daniel Boller & Michael Lechner & Gabriel Okasa, 2021.
"The Effect of Sport in Online Dating: Evidence from Causal Machine Learning,"
Papers
2104.04601, arXiv.org.
- Boller, Daniel & Lechner, Michael & Okasa, Gabriel, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Economics Working Paper Series 2104, University of St. Gallen, School of Economics and Political Science.
- Boller, Daniel & Lechner, Michael & Okasa, Gabriel, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," IZA Discussion Papers 14259, Institute of Labor Economics (IZA).
- Daniel Jacob, 2021. "CATE meets ML -- The Conditional Average Treatment Effect and Machine Learning," Papers 2104.09935, arXiv.org, revised Apr 2021.
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-EXP-2024-01-08 (Experimental Economics)
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:eti:dpaper:23081. 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: TANIMOTO, Toko (email available below). General contact details of provider: https://edirc.repec.org/data/rietijp.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.