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Articles

Conducting a rigorous quasi‐experimental evaluation using a school district’s existing student database

Pages 69-88 | Received 08 Aug 2008, Accepted 01 Dec 2008, Published online: 18 Mar 2009

References

  • Allison , P.D. 2001 . Missing data , (Sage University Papers Series on Quantitative Applications in Social Sciences, 07‐136) Thousand Oaks, CA : Sage .
  • Barnow , B.S. , Cain , G.G. and Goldberger , A.S. 1980 . Issues in the analysis of selectivity bias . Evaluation Studies Review Annual , 5 : 43 – 59 .
  • Borman , G.D. 2002 . Experiments for educational evaluation and improvement . Peabody Journal of Education , 77 ( 4 ) : 7 – 27 .
  • Boruch , R. 1997 . Randomized experiments for planning and evaluation: A practical guide , Thousand Oaks, CA : Sage .
  • Cohen , J. 1988 . Statistical power analysis for the behavioral sciences , 2nd ed. , Hillsdale, NJ : Erlbaum .
  • Cook , T.D. and Payne , M.R. 2002 . “ Objecting to the objections to using random assignment in educational research ” . In Evidence matters: Randomized trails in educational research , Edited by: Mosteller , F. and Boruch , R. 150 – 78 . Washington, DC : Brookings Institute .
  • Heckman , J.J. 1976 . 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 Measurements , 5 : 475 – 92 .
  • Ho , D.E. , Imai , K. , King , G. and Stuart , E. 2007 . Matching as a nonparametric preprocessing for reducing model dependence in parametric causal inference . Political Analysis , 15 ( 3 ) : 199 – 36 .
  • King , G. , Honaker , J. , Joseph , A. and Scheve , K. 2001 . Analyzing incomplete political science data: An alternative algorithm for multiple imputation . American Political Science Review , 95 ( 1 ) : 49 – 69 .
  • Kruskal , W. 1980 . The significance of Fisher . Journal of the American Statistical Association , 75 ( 372 ) : 1019 – 30 .
  • Leow , C. , Marcus , S. , Zanutto , E. and Boruch , R. 2004 . Effects of advanced course‐taking on math and science achievement: Addressing selection bias using propensity scores . American Journal of Evaluation , 25 ( 4 ) : 461 – 78 .
  • Rosenbaum , P.R. 1995 . Observational studies , New York : Springer‐Verlag .
  • Rosenbaum , P.R. 1998 . “ Propensity score ” . In Encyclopedia of biostatistics , Edited by: Armitage , P. and Colton , T. 3551 – 5 . New York : John Wiley .
  • Rosenbaum , P.R. and Rubin , D.B. 1983 . The central role of the propensity score in observational studies for causal effects . Biometrika , 70 ( 1 ) : 41 – 55 .
  • Rosenbaum , P.R. and Rubin , D.B. 1985 . Constructing a control group using multivariate matched sampling methods that incorporate the propensity score . American Statistician , 39 ( 1 ) : 33 – 8 .
  • Rubin , D.B. 1974 . Estimating causal effects of treatments in randomized and nonrandomized studies . Journal of Educational Psychology , 66 ( 5 ) : 688 – 701 .
  • Rubin , D.B. 1987 . Multiple imputation for nonresponse in surveys , New York : John Wiley .
  • Rubin , D.B. and Thomas , N. 2000 . Combining propensity score matching with additional adjustments for prognostic covariates . Journal of American Statistical Association , 95 : 573 – 85 .
  • Schneider , B. , Carnoy , M. , Kilpatrick , J. , Schmidt , W.H. and Shavelson , R.J. 2007 . Estimating causal effects using experimental and observational designs , Washington, DC : American Educational Research Association . (Report from the Governing Board of the American Educational Research Association Grants Program)
  • Shadish , W.R. , Cook , T.D. and Campbell , D.T. 2002 . Experimental and quasi‐experimental designs for generalized causal inference , Boston, MA : Houghton Mifflin .
  • Spybrook , J. , Raudenbush , S.W. , Liu , X. , Congdon , R. and Martinez , A. 2008 . Optimal design for longitudinal and multilevel research: Documentation for the ‘Optimal Design’ software http://sitemaker.umich.edu/group-based/optimal_design_software (accessed February 11, 2009)
  • Singer , J. 1998 . Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models . Journal of Educational and Behavioral Statistics , 24 ( 4 ) : 323 – 35 .
  • U.S. Department of Education . 2007 . Report of the Academic Competitiveness Council http://www.ed.gov/about/inits/ed/competitiveness/acc-mathscience/report.pdf (accessed August 7, 2007)
  • What Works Clearinghouse . n.d. . Standards http://ies.ed.gov/ncee/wwc/references/standards/ (accessed February 11, 2009)

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