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Early Childhood Education and Adult Depression: An Attrition Reanalysis With Inverse Propensity Score Weighting

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  • Christina F. Mondi
  • Arthur J. Reynolds
  • Brandt A. Richardson

Abstract

In a previous study of the Child-Parent Centers (CPC) education program, preschool participation was linked to a 4.6 percentage point reduction (26%) in depressive symptoms at ages 22–24 over the matched comparison group enrolling the usual programs. The present study reanalyzed these data in the Chicago Longitudinal Study to address potential attrition bias since more than a quarter of the sample was missing on the outcome. Using inverse probability weighting (IPW) involving 32 predictors of sample retention, findings for the 1,142 participants growing up in high-poverty neighborhoods indicated that CPC participation was associated with a 7.1 percentage point reduction (95% CI = [−9.7, −5.4]) in one or more depressive symptoms (39% reduction over the comparison group). Although this marginal effect was within the confidence interval of the original study (95% CI = [−9.5, 0.3]), the 54% increase in the point estimate is substantial and of practical significance, suggesting underestimation in the prior study. Alternative analysis of different predictors and IPW models, including adjustments for program selection and attrition together, yielded similar results. Findings indicate that high-quality early childhood programs continue to be an important strategy for the prevention of depression and its debilitating effects on individuals and families.

Suggested Citation

  • Christina F. Mondi & Arthur J. Reynolds & Brandt A. Richardson, 2020. "Early Childhood Education and Adult Depression: An Attrition Reanalysis With Inverse Propensity Score Weighting," Evaluation Review, , vol. 44(5-6), pages 379-409, October.
  • Handle: RePEc:sae:evarev:v:44:y:2020:i:5-6:p:379-409
    DOI: 10.1177/0193841X20976527
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    References listed on IDEAS

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    1. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    2. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    3. Arthur J. Reynolds & Judy A. Temple, 1995. "Quasi-Experimental Estimates of the Effects of a Preschool Intervention," Evaluation Review, , vol. 19(4), pages 347-373, August.
    4. 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.
    5. Arteaga, Irma & Humpage, Sarah & Reynolds, Arthur J. & Temple, Judy A., 2014. "One year of preschool or two: Is it important for adult outcomes?," Economics of Education Review, Elsevier, vol. 40(C), pages 221-237.
    6. William T. Gormley, & Deborah Phillips & Sara Anderson, 2018. "The Effects of Tulsa's Pre†K Program on Middle School Student Performance," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 37(1), pages 63-87, January.
    7. J. A. Temple & A. J. Reynolds & W. T. Miedel, "undated". "Can Early Intervention Prevent High School Dropout? Evidence from the Chicago Child-Parent Centers," Institute for Research on Poverty Discussion Papers 1180-98, University of Wisconsin Institute for Research on Poverty.
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