Does non-participation in preschool affect children’s reading achievement? International evidence from propensity score analyses

Large-Scale Assessments in Education - Tập 4 Số 1 - 2016
Nina Hogrebe1, Rolf Strietholt2,3,4
1Department of Education, University of Münster, Münster, Germany
2Centre for Educational Measurement, University of Oslo, Oslo, Norway
3Department of Education and Special Education, University of Gothenburg, Gothenburg, Sweden
4Institute for School Development Research, Technische Universität Dortmund, Dortmund, Germany

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Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton, NJ: Princeton University Press.

Austin, P. C. (2009). Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in Medicine, 28(25), 3083–3107. doi: 10.1002/sim.3697 .

Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46(3), 399–424. doi: 10.1080/00273171.2011.568786 .

Barnett, W. S. (2011). Effectiveness of early education interventions. Science, 333(6045), 975–978. doi: 10.1126/science.1204534 .

Bos, W., Tarelli, I., Bremerich-Vos, A., & Schwippert, K. (Eds.). (2012). IGLU 2011—Lesekompetenzen von Grundschulkindern in Deutschland im internationalen Vergleich (Reading competencies of primary school children in German from an international comparative perspective). Münster: Waxmann.

Bronfenbrenner, U. (1979). The ecology of human development. Cambridge, MA: Harvard University Press.

Bronfenbrenner, U. (1990). The ecology of cognitive development. Zeitschrift für Sozialisationsforschung und Erziehungssoziologie, 10(2), 101–114.

Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In W. Damon & R. M. Lerner (Eds.), Handbook of child psychology ((Series Ed.) 6 ed., Vol. 1, pp. 793–828). New York, NY: Wiley.

Burger, K. (2010). How does early childhood care and education affect cognitive development? An international review of the effects of early interventions for children from different social backgrounds. Early Childhood Research Quarterly, 25(2), 140–165. doi: 10.1016/j.ecresq.2009.11.001 .

Buuren, S. V., & Groothuis-Oudshoorn, K. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3). Retrieved from http://www.jstatsoft.org/v45/i03 .

Camilli, G., Vargas, S., Ryan, S., & Barnett, B. (2010). Meta-analysis of the effects of early education interventions on cognitive and social development. Teachers College Record, 112(3), 579–620. Retrieved from http://www.tcrecord.org/Content.asp?ContentId=15440 .

Campbell, F. A., & Ramey, C. T. (1994). Effects of early intervention on intellectual and academic achievement: A follow-up study of children from low-income families. Child Development, 65(2), 684–698. doi: 10.1111/j.1467-8624.1994.tb00777.x .

Card, N. A. (2012). Applied meta-analysis for social science research. New York, NY: Guilford Press.

Chambers, B., Cheung, A., Slavin, R. E., Smith, D., & Laurenzano, M. (2010). Effective early childhood education programs: A systematic review. Retrieved from the Best Evidence Encyclopedia website: http://www.bestevidence.org/word/early_child_ed_Sep_22_2010.pdf .

Davier, M. v., Gonzales, E. J., & Mislevy, R. J. (2009). What are plausible values and why are they useful? In: IERI Monograph Series: Issues and Methodologies in Large-Scale Assessments (Vol. 2, pp. 9-36). Hamburg/Princeton NJ: IEA-ETS Research Institute.

DuGoff, E. E., Schuler, M., & Stuart, E. A. (2014). Generalizing observational study results: Applying propensity score methods to complex surveys. Health Services Research, 49(1), 284–303. doi: 10.1111/1475-6773.12090 .

Duncan, G. J., & Magnusson, K. (2013). Investing in preschool programs. Journal of Economic Perspectives, 27(2), 109–132. doi: 10.1257/jep.27.2.109 .

Early, D. M., & Burchinal, M. R. (2001). Early childhood care: Relations with family characteristics and preferred care characteristics. Early Childhood Research Quarterly, 16(4), 475–497. doi: 10.1016/S0885-2006(01)00120-X .

Foy, P., & Kennedy, A. M. (Eds.). (2008). PIRLS 2006 user guide for the international database. Chestnut Hill, MA: Boston College.

Grogan, K. E. (2012). Parents’ choice of pre-kindergarten: the interaction of parent, child and contextual factors. Early Child Development and Care, 182(10), 1265–1287. doi: 10.1080/03004430.2011.608127 .

Harder, V. S., Stuart, E. A., & Anthony, J. C. (2010). Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research. Psychological Methods, 15(3), 234–249. doi: 10.1037/a0019623 .

Heckman, J. J., & Robb, R. (1986). Alternative methods for solving the problem of selection bias in evaluating the impact of treatments on outcomes. In H. Wainer (Ed.), Drawing inferences from self-selected samples (pp. 63–107). New York, NY: Springer.

Hirshberg, D., Huang, D. S.-C., & Fuller, B. (2005). Which low-income parents select child-care? Family demand and neighborhood organizations. Children and Youth Services Review, 27(10), 1119–1148. doi: 10.1016/j.childyouth.2004.12.029 .

Ho, D., Imai, K., King, G., & Stuart, E. (2011). MatchIt: Nonparametric preprocessing for parametric causal inference. Journal of Statistical Software. Retrieved from http://gking.harvard.edu/matchit .

Hynes, K., & Habasevich-Brooks, T. (2008). The ups and downs of child care: Variations in child care quality and exposure across the early years. Early Childhood Research Quaterly, 23(4), 59–574. doi: 10.1016/j.ecresq.2008.09.001 .

Imai, K., & van Dyk, D. A. (2004). Causal inference with general treatment regimes: Generalizing the propensity score. Journal of the American Statististical Association, 99(467), 854–866. doi: 10.1198/016214504000001187 .

Imbens, G. W. (2000). The role of the propensity score in estimating dose-response functions. Biometrika, 87(3), 706–710. doi: 10.1093/biomet/87.3.706 .

Imbens, G. W. (2004). Nonparametric estimation of average treatment effects under exogeneity: A review. The Review of Economics and Statistics, 86(1), 4–29. doi: 10.3386/t0294 .

Imbens, G. W., & Rubin, D. B. (2015). Causal inference for statistics, social, and biomedical sciences. An introduction. New York, NY: Cambridge University Press.

Kim, J., & Fram, M. S. (2009). Profiles of choice: Parents’ patterns of priority in child care decision-making. Early Childhood Research Quarterly, 24(1), 77–91. doi: 10.1016/j.ecresq.2008.10.001 .

Kirsch, I., Lennon, M., von Davier, M., Gonzalez, E., & Yamamoto, K. (2013). On the growing importance of international large-scale assessments. In M. von Davier, E. Gonzalez, I. Kirsch, & K. Yamamoto (Eds.), The role of international large-scale assessments: Perspectives from technology, economy, and educational research (pp. 1–11). Dordrecht, The Netherlands: Springer.

Knudsen, E. I., Heckman, J. J., Cameron, J. L., & Shonkoff, J. P. (2006). Economic, neurobiological, and behavioral perspectives on building America’s future workforce. Proceedings of the National Academy of Sciences, 27, 10155–10162. doi: 10.1073/pnas.0600888103 .

Liu, W., Kuramoto, S. J., & Stuart, E. A. (2013). An introduction to sensitivity analysis for unobserved confounding in nonexperimental prevention research. Prevention Science, 14(6), 570–580. doi: 10.1007/s11121-012-0339-5 .

Lohr, S. L. (2010). Sampling: Design and analysis (2nd ed.). Boston, MA: Brooke/Cole.

Lumley, T. (2014). Survey: analysis of complex survey samples. R package version, 3.30.

Martin, M. O., & Mullis, I. V. S. (Eds.). (2012). Methods and procedures in TIMSS and PIRLS 2011. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.

McCaffrey, D. F., Griffin, B. A., Almirall, D., Slaughter, M. E., Ramchand, R., & Burgette, L. F. (2013). A tutorial on propensity score estimation for multiple treatments using generalized boosted models. Statistics in Medicine, 32(19), 3388–3414. doi: 10.1002/sim.5753 .

Montie, J. E. (2011). Thr growth and developmet of the preprimary project. In C. Papanastasiou, T. Plomp, & E. C. Papanastasiou (Eds.), IEA 1958–2008: 50 years experiences and memories (Vol. 1, pp. 165–185). Nicosia: Cultural Center of the Kykkos Monastery.

Müller, N., Strietholt, R., & Hogrebe, N. (2014). Ungleiche Zugänge zum Kindergarten (Unequal access to preschool). In K. Drossel, R. Strietholt, & W. Bos (Eds.), Empirische Bildungsforschung und evidenzbasierte Reformen im Bildungswesen (pp. 33–46). Münster: Waxmann.

Mullis, I. V. S., Martin, M. O., Foy, P., & Drucker, K. T. (2012). PIRLS 2011. International results in reading. Retrieved from http://timssandpirls.bc.edu/pirls2011/international-results-pirls.html .

Organization for Economic Development and Cooperation (OECD). (2013). PISA 2012 Results: Excellence through equity: Giving every student the chance to succeed (Vol. II). Paris: OECD Publishing.

Pianta, R., Barnett, W., Burchinal, M., & Thornburg, K. (2009). The effects of preschool education: What we know, how public policy is or is not aligned with the evidence base, and what we need to know. Psychological Science in the Public Interest, 10(2), 49–88. doi: 10.1177/1529100610381908 .

Puma, M., Bell, S., Cook, R., Heid, C., Broene, P., Jenkins, F., Mashburn, A., & Downer, J., (2012). Third grade follow-up to the Head Start impact study. Final report (OPRE report no. 2012-45). Retrieved from the Administration for Children and Families, US Department of Health and Human Services website: http://www.acf.hhs.gov/sites/default/files/opre/head_start_report.pdf .

Rosenbaum, P. R. (2002). Observational studies (2nd ed.). New York, NY: Springer.

Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. doi: 10.1093/biomet/70.1.41 .

Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688–701. doi: 10.1037/h0037350 .

Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York, NY: Wiley.

Rubin, D. B. (2001). Using propensity scores to help design observational studies: Application to the tobacco litigation. Health Services and Outcomes Research Methodology, 2(3–4), 169–188. doi: 10.1023/A:1020363010465 .

Rutkowski, L., Gonzales, E. J., Joncas, M., & von Davier, M. (2010). International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142–151. doi: 10.3102/0013189X10363170 .

Schleicher, A. (2014). Equity, excellence and inclusiveness in education: Policy lessons from around the world. Paris: OECD Publishing.

Schweinhart, L. J., Montie, J., Xiang, Z., Barnett, W. S., & Nores, M. (2005). Lifetime effects: The high/scope perry preschool study through age 40. Ypsilanti, MO: High/Scope Press.

Strietholt, R., Gustafsson, J.-E., Rosèn, M., & Bos, W. (2014). Outcomes and causal inference in international comparative assessments. In R. Strietholt, W. Bos, J.-E. Gustafsson, & M. Rosén (Eds.), Educational policy evaluation through international comparative assessments (pp. 10–18). Münster: Waxmann.

Stuart, E. A. (2007). Estimating causal effects using school-level datasets. Educational Researcher, 36(4), 187–198. doi: 10.3102/0013189X07303396 .

Stuart, E. A. (2010). Matching methods for causal inference: A review and look forward. Statistical Science, 25(1), 1-21. doi: 10.1214/09-STS313 .

Sylva, K., Melhuish, E., Sammons, P., Siraj-Blatchford, I., & Taggart, B. (2008). The effective provision of pre-school education (EPPE) project: Final report from the primary phase: Pre-school, school and family influences on children’s development during key stage 2 (Age 7–11). Retrieved from the Institute of Education, University of London website: http://www.ioe.ac.uk/End_of_primary_school_phase_report.pdf .

UNESCO. (2006). Strong foundations: Early childhood care and education. Paris: UNESCO.

UNESCO. (2012). International standard classification of education: ISCED 2011. Retrieved from the UNESCO Institute for Statistics website: http://www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx .

Vandenbroeck, M., De Visscher, S., Van Nuffel, K., & Ferla, J. (2008). Mothers’ search for infant child care: The dynamic relationship between availability and desirability in a continental European welfare state. Early Childhood Research Quarterly, 23(2), 245–258. doi: 10.1016/j.ecresq.2007.09.002 .

VanderWeele, T. J., & Arah, O. A. (2011). Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders. Epidemiology, 22(1), 42–52. doi: 10.1097/EDE.0b013e3181f74493 .

Vogel, C. A., Xue, Y., Moiduddin, E. M., Carlson, B. L., & Kisker, E. E. (2010). Early Head Start children in grade 5: Long-term follow-up of the Early Head Start Research and Evaluation Study sample (OPRE report no. 2011-8). Retrieved from the Office of Planning, Research, and Evaluation, Administration for Children and Families, US Department of Health and Human Services website: http://www.acf.hhs.gov/programs/opre/resource/early-head-start-children-in-grade-5-long-term-followup-of-the-early-head .

Zachrisson, H. D., Janson, H., & Nærde, A. (2013). Predicting early center care utilization in a context of universal access. Early Childhood Research Quarterly, 28(1), 74–82. doi: 10.1016/j.ecresq.2012.06.004 .