Can Nonexperimental Methods Provide Unbiased Estimates of a Breastfeeding Intervention? A Within-Study Comparison of Peer Counseling in Oregon
Author
Abstract
Suggested Citation
DOI: 10.1177/0193841X19865963
Download full text from publisher
References listed on IDEAS
- James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
- Shadish, William R. & Clark, M. H. & Steiner, Peter M., 2008. "Can Nonrandomized Experiments Yield Accurate Answers? A Randomized Experiment Comparing Random and Nonrandom Assignments," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1334-1344.
- Burt S. Barnow & Coady Wing & M. H. Clark, 2017. "What Can We Learn From A Doubly Randomized Preference Trial?—An Instrumental Variables Perspective," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 36(2), pages 418-437, March.
- Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
- A. Smith, Jeffrey & E. Todd, Petra, 2005.
"Does matching overcome LaLonde's critique of nonexperimental estimators?,"
Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
- Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20035, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Thomas D. Cook & William R. Shadish & Vivian C. Wong, 2008. "Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 724-750.
- LaLonde, Robert J, 1986.
"Evaluating the Econometric Evaluations of Training Programs with Experimental Data,"
American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
- Robert J. LaLonde, 1984. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," Working Papers 563, Princeton University, Department of Economics, Industrial Relations Section..
- James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
- Long, Qi & Little, Roderick J. & Lin, Xihong, 2008.
"Causal Inference in Hybrid Intervention Trials Involving Treatment Choice,"
Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 474-484, June.
- Qi Long & Rod Little & Xihong Lin, 2004. "Causal Inference in Hybrid Intervention Trials Involving Treatment Choice," The University of Michigan Department of Biostatistics Working Paper Series 1033, Berkeley Electronic Press.
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.- Guido W. Imbens & Jeffrey M. Wooldridge, 2009.
"Recent Developments in the Econometrics of Program Evaluation,"
Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
- Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
- Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
- Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute of Labor Economics (IZA).
- Lechner, Michael & Wunsch, Conny, 2013.
"Sensitivity of matching-based program evaluations to the availability of control variables,"
Labour Economics, Elsevier, vol. 21(C), pages 111-121.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables," IZA Discussion Papers 5553, Institute of Labor Economics (IZA).
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of matching-based program evaluations to the availability of control variables," Economics Working Paper Series 1105, University of St. Gallen, School of Economics and Political Science.
- Michael Lechner & Conny Wunsch, 2011. "Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables," CESifo Working Paper Series 3381, CESifo.
- Lechner, Michael & Wunsch, Conny, 2011. "Sensitivity of matching-based program evaluations to the availability of control variables," CEPR Discussion Papers 8294, C.E.P.R. Discussion Papers.
- Yonatan Eyal, 2020. "Self-Assessment Variables as a Source of Information in the Evaluation of Intervention Programs: A Theoretical and Methodological Framework," SAGE Open, , vol. 10(1), pages 21582440198, January.
- Wichman, Casey J. & Ferraro, Paul J., 2017. "A cautionary tale on using panel data estimators to measure program impacts," Economics Letters, Elsevier, vol. 151(C), pages 82-90.
- Ravallion, Martin, 2008.
"Evaluating Anti-Poverty Programs,"
Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 59, pages 3787-3846,
Elsevier.
- Ravallion, Martin, 2005. "Evaluating anti-poverty programs," Policy Research Working Paper Series 3625, The World Bank.
- Vivian C. Wong & Peter M. Steiner & Kylie L. Anglin, 2018. "What Can Be Learned From Empirical Evaluations of Nonexperimental Methods?," Evaluation Review, , vol. 42(2), pages 147-175, April.
- Andrew P. Jaciw, 2016. "Assessing the Accuracy of Generalized Inferences From Comparison Group Studies Using a Within-Study Comparison Approach," Evaluation Review, , vol. 40(3), pages 199-240, June.
- Iacus, Stefano M. & Porro, Giuseppe, 2007. "Missing data imputation, matching and other applications of random recursive partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 773-789, October.
- David McKenzie & John Gibson & Steven Stillman, 2010.
"How Important Is Selection? Experimental vs. Non-Experimental Measures of the Income Gains from Migration,"
Journal of the European Economic Association, MIT Press, vol. 8(4), pages 913-945, June.
- David McKenzie & Steven Stillman & John Gibson, 2010. "How Important is Selection? Experimental VS. Non‐Experimental Measures of the Income Gains from Migration," Journal of the European Economic Association, European Economic Association, vol. 8(4), pages 913-945, June.
- David McKenzie & John Gibson & Steven Stillman, 2006. "How Important is Selection? Experimental vs Non-experimental Measures of Income Gains from Migration," Working Papers in Economics 06/03, University of Waikato.
- McKenzie, David & Gibson, John & Stillman, Steven, 2006. "How Important Is Selection? Experimental vs. Non-Experimental Measures of the Income Gains from Migration," IZA Discussion Papers 2087, Institute of Labor Economics (IZA).
- Katherine Baicker & Theodore Svoronos, 2019. "Testing the Validity of the Single Interrupted Time Series Design," NBER Working Papers 26080, National Bureau of Economic Research, Inc.
- McKenzie, David & Gibson, John & Stillman, Steven, 2006. "How important is selection ? Experimental versus non-experimental measures of the income gains from migration," Policy Research Working Paper Series 3906, The World Bank.
- Flores, Carlos A. & Mitnik, Oscar A., 2009.
"Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data,"
IZA Discussion Papers
4451, Institute of Labor Economics (IZA).
- Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-9, University of Miami, Department of Economics.
- Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
- Jochen Kluve & Boris Augurzky, 2007.
"Assessing the performance of matching algorithms when selection into treatment is strong,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 533-557.
- Augurzky, Boris & Kluve, Jochen, 2004. "Assessing the Performance of Matching Algorithms When Selection into Treatment Is Strong," IZA Discussion Papers 1301, Institute of Labor Economics (IZA).
- Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007.
"Using State Administrative Data to Measure Program Performance,"
The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
- Peter R. Mueser & Kenneth Troske & Alexey Gorislavsky, 2003. "Using State Administrative Data to Measure Program Performance," Working Papers 0309, Department of Economics, University of Missouri.
- Mueser, Peter R. & Troske, Kenneth & Gorislavsky, Alexey, 2003. "Using State Administrative Data to Measure Program Performance," IZA Discussion Papers 786, Institute of Labor Economics (IZA).
- Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," Working Papers 0702, Department of Economics, University of Missouri.
- Hugo Ñopo, 2008.
"Matching as a Tool to Decompose Wage Gaps,"
The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 290-299, May.
- Hugo Nopo, 2003. "Matching as a Tool to Decompose Wage Gaps," Middlebury College Working Paper Series 0406, Middlebury College, Department of Economics.
- Nopo, Hugo R., 2004. "Matching as a Tool to Decompose Wage Gaps," IZA Discussion Papers 981, Institute of Labor Economics (IZA).
- Giuseppe Porro & Stefano Maria Iacus, 2009.
"Random Recursive Partitioning: a matching method for the estimation of the average treatment effect,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 163-185.
- Stefano Iacus & Giuseppe Porro, 2006. "Random recursive partitioning: a matching method for the estimation of the average treatment effect," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1018, Universitá degli Studi di Milano.
- Ferraro, Paul J. & Miranda, Juan José, 2014. "The performance of non-experimental designs in the evaluation of environmental programs: A design-replication study using a large-scale randomized experiment as a benchmark," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 344-365.
- David McKenzie & John Gibson & Steven Stillman, 2006. "How Important is Selection? Experimental vs Non-experimental Measures of the Income Gains of Migration," Working Papers 06_02, Motu Economic and Public Policy Research.
- Ben Weidmann & Luke Miratrix, 2021. "Lurking Inferential Monsters? Quantifying Selection Bias In Evaluations Of School Programs," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(3), pages 964-986, June.
- Giuseppe PORRO & Stefano Maria IACUS, 2004. "Average treatment effect estimation via random recursive partitioning," Departmental Working Papers 2004-28, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
More about this item
Keywords
breasfeeding; RCT; WIC; WSC;All these keywords.
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:sae:evarev:v:43:y:2019:i:3-4:p:152-188. 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: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.