EVALUATION OF THE EFFECTS OF TWO EARLY CHILDHOOD INTERVENTIONS ON ADULTHOOD INCOME: EXAMINING THE ASSOCIATION OF PROXIMAL AND DISTAL INTERVENTION EFFECTS WITH SUBJECT-LEVEL HETEROGENEITY
Loading...
Links to Files
Permanent Link
Author/Creator
Author/Creator ORCID
Date
2019-01-01
Type of Work
Department
School of Public Policy
Program
Public Policy
Citation of Original Publication
Rights
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
Abstract
The long-term evaluation and subsequent replication of early childhood interventions can be costly. Thus, approaches that maximize the efficiency of these tasks are critical to the economic feasibility of such interventions. I use longitudinal data from the Johns Hopkins University (JHU) Prevention Research Center (PRC) intervention trials to: (a) evaluate the impact of two randomized classroom-based early childhood interventions - the Good Behavior Game (GBG) and Mastery Learning (ML) - on adulthood income, and (b) explore the role of various forms of subject-level heterogeneity in the impact of these interventions on adulthood income. My dissertations centers around three core empirical analyses: (#1) Empirical evaluation of the effects of the GBG and ML interventions on adulthood income: testing a recursive model of proximal and distal effects vs. a reduced-form model of distal effects; (#2) Empirical evaluation of subject-level heterogeneity in sociodemographic and behavioral characteristics and their influence on the effects of the ML and GBG interventions on adulthood income; (#3) Empirical evaluation of subject-level heterogeneity in polygenic propensity for educational attainment and its influence on the effects of the ML and GBG interventions on adulthood income. In each analysis, I use multivariable generalized linear models to test my statistical hypotheses. In sensitivity analyses, I apply inverse probability of attrition weights to address longitudinal loss to follow-up. I find that universally, the ML and GBG interventions do not appear to have a significant impact on adulthood income. However, the ML intervention increased the probability of adulthood employment. The impact of these interventions, particularly the ML, varied by sociodemographic and behavioral heterogeneity and by polygenic propensity for educational attainment. Proximal measures of young adulthood educational attainment were strongly predictive of adulthood income and employment and therefore may serve as a proximal marker of distal intervention success. Aside from the interventions, participants' grade 1 global Teacher Observation of Classroom Adaptation - Revised (TOCA-R rating), grade 1 free lunch status, and EduYears GPS (a score summarizing the polygenic propensity for educational attainment) for the were remarkably predictive of adulthood income and employment outcomes, and these factors may be ideal for targeting at-risk populations for interventions.