Search Results

Source: Evaluation Review
Resulting in 3 citations.
1. Leite, Walter L.
Aydin, Burak
Cetin-Berber, Dee D.
Imputation of Missing Covariate Data Prior to Propensity Score Analysis: A Tutorial and Evaluation of the Robustness of Practical Approaches
Evaluation Review published online (22 June 2021): DOI: 10.1177/0193841X211020245.
Also: https://journals.sagepub.com/doi/full/10.1177/0193841X211020245
Cohort(s): Children of the NLSY79, NLSY79
Publisher: Sage Publications
Keyword(s): Breastfeeding; Child Care; Maternal Employment; Missing Data/Imputation; Monte Carlo; Propensity Scores

Permission to reprint the abstract has not been received from the publisher.

Objectives: The objectives of this study are to review MI-within, MI-across, and SI approaches to handle missing data on covariates prior to PSA, investigate the robustness of MI-across and SI with a Monte Carlo simulation study, and demonstrate the analysis of missing data and PSA with a step-by-step illustrative example.

Research design: The Monte Carlo simulation study compared strategies to impute missing data in continuous and categorical covariates for estimation of propensity scores. Manipulated conditions included sample size, the number of covariates, the size of the treatment effect, missing data mechanism, and percentage of missing data. Imputation strategies included MI-across and SI by joint modeling or multivariate imputation by chained equations (MICE).

Results: The results indicated that the MI-across method performed well, and SI also performed adequately with smaller percentages of missing data. The illustrative example demonstrated MI and SI, propensity score estimation, calculation of propensity score weights, covariate balance evaluation, estimation of the average treatment effect on the treated, and sensitivity analysis using data from the National Longitudinal Survey of Youth.

Bibliography Citation
Leite, Walter L., Burak Aydin and Dee D. Cetin-Berber. "Imputation of Missing Covariate Data Prior to Propensity Score Analysis: A Tutorial and Evaluation of the Robustness of Practical Approaches." Evaluation Review published online (22 June 2021): DOI: 10.1177/0193841X211020245.
2. Murnane, Richard J.
Willett, John B.
Boudett, Kathryn Parker
Do Male Dropouts Benefit from Obtaining a GED, Postsecondary Education, and Training?
Evaluation Review 23,5 (October 1999): 475-503
Cohort(s): NLSY79
Publisher: Sage Publications
Keyword(s): GED/General Educational Diploma/General Equivalency Degree/General Educational Development; High School Dropouts; Schooling, Post-secondary; Skills; Training; Training, Employee; Wages

Permission to reprint the abstract has not been received from the publisher.

The authors use longitudinal data from the National Longitudinal Survey of Youth to investigate whether the wage trajectories of male high school dropouts are affected by the acquisition of the General Educational Development (GED) credential, by postsecondary education, and by training. The authors show that acquisition of the GED results in wage increases for dropouts who left school with weak skills, but not for dropouts who left high school with stronger skills. College and training provided by employers are associated with higher wages for male dropouts.
Bibliography Citation
Murnane, Richard J., John B. Willett and Kathryn Parker Boudett. "Do Male Dropouts Benefit from Obtaining a GED, Postsecondary Education, and Training?" Evaluation Review 23,5 (October 1999): 475-503.
3. Scott-Clayton, Judith
Wen, Qiao
Estimating Returns to College Attainment: Comparing Survey and State Administrative Data–Based Estimates
Evaluation Review 43, 5 (October 2019): 266-306.
Also: https://journals.sagepub.com/doi/full/10.1177/0193841X18803247
Cohort(s): NLSY97
Publisher: Sage Publications
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; College Enrollment; Earnings; Educational Attainment; Educational Returns; Geocoded Data; Migration Patterns; Mobility

Permission to reprint the abstract has not been received from the publisher.

Objectives: In this article, we use recent waves of data from the National Longitudinal Survey of Youth 1997 to provide new, nationally representative, nonexperimental estimates of the returns to degrees, as well as to assess the possible limitations of single-state, administrative data–based estimates.

Research design: To do this, we explore the sensitivity of estimated returns to college, by testing different sample restrictions, inclusion of different sets of covariates, and alternative ways of treating out-of-state earnings to approximate the real-world limitations of state administrative databases.

Results: We find that failure to control for measures of student ability leads to upward bias, while limiting the sample to college enrollees only leads to an understatement of degree returns. On net, these two biases roughly balance out, suggesting that administrative data-based estimates may reasonably approximate true returns.

Conclusions: We conclude with a discussion of the relative advantages and disadvantages of survey versus administrative data for estimating returns to college as well as implications for research and policy efforts based upon single-state administrative databases.

Bibliography Citation
Scott-Clayton, Judith and Qiao Wen. "Estimating Returns to College Attainment: Comparing Survey and State Administrative Data–Based Estimates." Evaluation Review 43, 5 (October 2019): 266-306.