Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition

Journal of Educational and Behavioral Statistics

Volumn 37, Issue 3, 2012, Pages 443-474

  Huber, Martin ^a  

^a UNIVERSITY OF ST GALLEN   (Switzerland)

Author keywords

attrition; experiments; inverse probability weighting

Indexed keywords

EID: 84865293006     PISSN: 10769986     EISSN: None     Source Type: Journal    
DOI: 10.3102/1076998611411917     Document Type: Article

References (74)

1. Ahn H.,Powell J.Semiparametric estimation of censored selection models with a nonparametric selection mechanism.Journal of Econometrics. 1993;58:3-29.
2. Angrist J.,Bettinger E.,Kremer M.Long-term educational consequence of secondary school vouchers: Evidence from administrative records in Colombia.American Economic Review. 2006;96:847-862.
3. Angrist J.,Lavy V.The effects of high stakes high school achievement awards: Evidence from a randomized trial.The American Economic Review. 2009;99:1384-1414.
4. Barnard J.,Frangakis C. E.,Hill J. L.,Rubin D. B.Principal stratification approach to broken randomized experiments: A case study of school choice vouchers in New York City.Journal of the American Statistical Association. 2003;98:299-311.
5. Bertrand M.,Duflo E.,Mullainathan S.How much should we trust differences-in-differences estimates?.The Quarterly Journal of Economics. 2004;119:249-275.
6. Bertrand M.,Mullainathan S.Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination.The American Economic Review. 2004;94:991-1013.
7. Bloom H.,Orr L.,Bell S.,Cave G.,Doolittle F.,Lin W.,Bos J.The benefits and costs of JTPA title II-A programs: Key findings from the National Job Training Partnership Act study.Journal of Human Resources. 1997;32:549-576.
8. Blundell R.,Powell J.Advances in economics and econometrics. Dewatripont L. H. M.Turnovsky S., ed. Cambridge, UK: Cambridge University Press; 2003:312-357.
9. Busso M.,DiNardo J.,McCrary J.Finite sample properties of semiparametric estimators of average treatment effects. 2009a:.
10. Busso M.,DiNardo J.,McCrary J.2009b:.
11. Card D.Handbook of labor economics. Ashenfelter O.Card D., ed. Amsterdam, Netherlands: North-Holland; 1999:1802-1863.
12. Castiglioni L.,Pforr K.,Krieger U.The effect of incentives on response rates and panel attrition: Results of a controlled experiment.Survey Research Methods. 2008;2:151-158.
13. Cochran W. G.,Chambers S. P.The planning of observational studies of human populations.Journal of the Royal Statistical Society Series A. 1965;128:234-265.
14. Crump R. K.,Hotz V. J.,Imbens G. W.,Mitnik O. A.Dealing with limited overlap in estimation of average treatment effects.Biometrika. 2009;96:187-199.
15. Das M.,Newey W. K.,Vella F.Nonparametric estimation of sample selection models.Review of Economic Studies. 2003;70:33-58.
16. Diamond A.,Sekhon J. S.Genetic matching for estimating causal effects: A general multivariate matching method for achieving balance in observational studies. Institute of Governmental Studies Working Paper. University of California, Berkeley; 2006:.
17. DiNardo J.,McCrary H.,Sanbonmatsu L.Constructive proposals for dealing with attrition: An empirical example. Ann Arbor: University of Michigan; 2006:.
18. Duflo E.Field experiments in development economics.Advances in economics and econometrics. 2006;Vol. 2:322-48.
19. Finn H. D.,Achilles C. M.Tennessee's class size study: Findings, implications, misconceptions.Educational Evaluation and Policy Analysis. 1999;21:97-109.
20. Fisher R.Statistical methods for research workers. Edinburgh, UK: Oliver and Boyd; 1925:.
21. Fisher R.The design of experiments. Edinburgh, UK: Oliver and Boyd; 1935:.
22. Fitzgerald J.,Gottschalk P.,Moffitt R.An analysis of sample attrition in panel data: The Michigan panel study of income dynamics.The Journal of Human Resources. 1998;33:251-299.
23. Frangakis C. E.,Rubin D. B.The defining role of principal stratification and effects for comparing treatments adjusted for posttreatment variables: From treatment noncompliance to surrogate endpoints.Biometrics. 2002;58:191-199.
24. Freedman D.Statistical models for causation: What inferential leverage do they provide.Evaluation Review. 2006;30:691-713.
25. Gertler P.Do conditional cash transfers improve child health? Evidence form PROGRESA's control randomized experiment.The American Economic Review. 2004;94:336-341.
26. Grilo C. M.,Money R.,Barlow D. H.,Goddard A. W.,Gorman J. M.,Hofmann S. G.,Woods S. W.Pretreatment patient factors predicting attrition from a multicenter randomized controlled treatment study for panic disorder.Comprehensive Psychiatry. 1998;39:323-332.
27. Grogger J.Bounding the effects of social experiments: Accounting for attrition in administrative data.mimeo. 2009;:.
28. Harrison G. W.,List J. A.Field experiments.Journal of Economic Literature. 2004;42:1009-1055.
29. Hausman J. A.,Wise D. A.Attrition bias in experimental and panel date: The Gary income maintenance experiment.Econometrica. 1979;47:455-473.
30. Heckman J. J.Shadow prices, market wages and labor supply.Econometric. 1974;42:679-694.
31. Heckman J. J.The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models.Annals of Economic and Social Measurement. 1976;5:475-492.
32. Heckman J. J.Sample selection bias as a specification error.Econometrica. 1979;47:153-161.
33. Heitjan D. F.,Basu S.Distinguishing missing at random and missing completely at random.The American Statisticia. 1996;50:207-213.
34. Hirano K.,Imbens G. W.,Ridder G.Efficient estimation of average treatment effects using the estimated propensity score.Econometrica. 2003;71:1161-1189.
35. Horowitz J.,Manski C. F.Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and Imputations.Journal of Econometrics. 1998;84:37-58.
36. Horowitz J.,Manski C. F.Nonparametric analysis of randomized experiments with missing covariate and outcome data.Journal of the American Statistical Association. 2000;95:77-84.
37. Horvitz D.,Thompson D.A generalization of sampling without replacement from a finite population.Journal of American Statistical Association. 1952;47:663-685.
38. Huber B.Treatment evaluation in the presence of sample selection (Department of Economics Discussion Paper no. 2009-07). Switzerland: University of St. Gallen; 2009:.
39. Huber M.,Lechner M.,Wunsch C.How to control for many covariates? Reliable estimators based on the propensity score. 2010:.
40. Imai K.Statistical analysis of randomized experiments with non-ignorable missing binary outcomes: An application to a voting experiment.Journal of the Royal Statistical Society Series C. 2009;58:83-104.
41. Imbens G. W.Nonparametric estimation of average treatment effects under exogeneity: A review.The Review of Economics and Statistics. 2004;86:4-29.
42. Imbens G. W.Better LATE than nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009). 2009:.
43. Imbens G. W.,Newey W.Identification and estimation of triangular simultaneous equations models without additivity.Econometrica. 2009;77:1481-1512.
44. Imbens G. W.,Wooldridge J. M.Recent developments in the econometrics of program evaluation.Journal of Economic Literature. 2009;47:5-86.
45. Karlan D.,List J. A.Does price matter in charitable giving? Evidence from a large-scale natural field experiment.The American Economic Review. 2007;97:1774-1793.
46. Krueger A. B.Experimental estimates of education production functions.Quarterly Journal of Economics. 1999;114:497-532.
47. Krueger A. B.,Zhu P.Another look at the New York City school voucher experiment.American Behavioral Scientist. 2004;47:658-698.
48. Lee D. S.Training, wages, and sample selection: Estimating sharp bounds on treatment effects.Review of Economic Studies. 2009;76:1071-1102.
49. Lee S.,Whang Y.-J.Nonparametric tests of conditional treatment effects. 2010;:.
50. Mealli F.,Pacini B.mimeo. 2008:.
51. Mulligan C. B.,Rubinstein Y.Selection, investment, and women's relative wages over time.Quarterly Journal of Economics. 2008;123:1061-1110.
52. Newey W. K.Nonparametric continuous/discrete choice models.International Economic Review. 2007;48:1429-1439.
53. Newey W. K.,Powell J. L.,Vella F.Nonparametric estimation of triangular simultaneous equations models.Econometrica. 1999;67:565-603.
54. Neyman J.On the application of probability theory to agricultural experiments. Essay on principles.Statistical Science. 1923;Reprint, 5:463-480.
55. Robins J.,Rotnitzky A.Semiparametric efficiency in multivariate regression models with missing data.Journal of American Statistical Association. 1995;90:122-129.
56. Robins J.,Rotnitzky A.,Zhao L.Analysis of semiparametric regression models for repeated outcomes in the presence of missing data.Journal of American Statistical Association. 1995;90:106-121.
57. Robins J.,Tsiatis A.Correcting for non-compliance in randomized trials using rank-preserving structural failure time models.Communications in Statistics. 1991;20:2069-2631.
58. Rosenbaum P. R.,Rubin D. B.The central role of the propensity score in observational studies for causal effects.Biometrika. 1983;70:41-55.
59. Rotnitzky A.,Robins J.Semiparametric regression estimation in the presence of dependent censoring.Biometrika. 1995;82:805-820.
60. Rubin D. B.Estimating causal effects of treatments in randomized and nonrandomized studies.Journal of Educational Psychology. 1974;66:688-701.
61. Rubin D. B.Inference and missing data.Biometrika. 1976;63:581-592.
62. Rubin D. B.Formalizing subjective notions about the effect of nonrespondents in sample surveys.Journal of the American Statistical Association. 1977;72:538-543.
63. Rubin D. B.Proceedings of the Survey Research Methods Section, American Statistical Association. Alexandria, VA: American Statistical Association; 1978:20-34.
64. Rubin D. B.Formal modes of statistical inference for causal effects.Journal of Statistical Planning and Inference. 1990;25:279-292.
65. Rubin D. B.Multiple imputation after 18+ Years.Journal of the American Statistical Association. 1996;91:473-489.
66. Rubin D. B.For objective causal inference, design trumps analysis.The Annals of Applied Statistics. 2008;2:808-840.
67. Scharfstein D. O.,Rotnitzky A.,Robins J. M.Adjusting for nonignorable drop-out using semiparametric nonresponse models.Journal of the American Statistical Association. 1999;94:1096-1120.
68. Schochet P. Z.,Burghardt J.,Glazerman S.National Job Corps study: The impacts of Job Corps on participants employment and related outcomes. Report. Washington, DC: Mathematica Policy Research; 2001:.
69. Shaikh A. M.,Simonsen M.,Vytlacil E. J.,Yildiz N.A specification test for the propensity score using its distribution conditional on participation.Journal of Econometrics. 2009;151:33-46.
70. Sianesi B.An evaluation of the Swedish system of active labour market programs in the 1990s.Review of Economics and Statistics. 2004;86:133-155.
71. Wooldridge J.Inverse probability weighted M-estimators for sample selection, attrition and stratification.Portuguese Economic Journal. 2002;1:141-162.
72. Wooldridge J.Inverse probability weighted estimation for general missing data problems.Journal of Econometrics. 2007;141:1281-1301.
73. Zhang J.,Rubin D. B.Estimation of causal effects via principal stratification when some outcome are truncated by death.Journal of Educational and Behavioral Statistics. 2003;28:353-368.
74. Zhang J.,Rubin D. B.,Mealli F.Advances in econometrics: Modelling and evaluating treatment effects in econometrics. Millimet D.Smith J.Vytlacil E., ed. New York, NY: Elsevier Science Ltd; 2008:117-145.