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Liyang Sun; Eli Ben-Michael; Avi Feller – Grantee Submission, 2024
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…
Descriptors: Evaluation Methods, Comparative Analysis, Computation, Data Analysis
Jennifer Hill; George Perrett; Vincent Dorie – Grantee Submission, 2023
Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…
Descriptors: Causal Models, Statistical Inference, Artificial Intelligence, Data Analysis
Enders, Craig K.; Hayes, Timothy; Du, Han – Grantee Submission, 2018
Literature addressing missing data handling for random coefficient models is particularly scant, and the few studies to date have focused on the fully conditional specification framework and "reverse random coefficient" imputation. Although it has not received much attention in the literature, a joint modeling strategy that uses random…
Descriptors: Data Analysis, Statistical Bias, Sample Size, Correlation
Wang, Chun; Nydick, Steven W. – Grantee Submission, 2019
Recent work on measuring growth with categorical outcome variables has combined the item response theory (IRT) measurement model with the latent growth curve (LGC) model (e.g., McArdle, 1988) and extended the assessment of growth to multidimensional IRT models (e.g., Hsieh, von Eye, & Maier, 2010; Huang, 2013) and higher-order IRT models…
Descriptors: Longitudinal Studies, Item Response Theory, Comparative Analysis, Models
Kaitlyn G. Fitzgerald; Elizabeth Tipton – Grantee Submission, 2022
As the body of scientific evidence about effective policies and practices grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Clearinghouses have emerged to facilitate the evidence-based decision-making process for education practitioners. While the results and methods for developing and analyzing…
Descriptors: Meta Analysis, Scientific Research, Evidence Based Practice, Decision Making
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Buzhardt, Jay; Greenwood, Charles R.; Jia, Fan; Walker, Dale; Schneider, Naomi; Larson, Anne L.; Valdovinos, Maria; McConnell, Scott R. – Grantee Submission, 2020
Data-driven decision making (DDDM) helps educators identify children not responding to intervention, individualize instruction, and monitor response to intervention in multitiered systems of support (MTSS). More prevalent in K-12 special education, MTSS practices are emerging in early childhood. In previous reports, we described the Making Online…
Descriptors: Data Analysis, Decision Making, Special Education, Infants
Roux, Anne M.; Shattuck, Paul T.; Rast, Jessica E.; Rava, Julianna A.; Edwards, Amy D.; Wei, Xin; McCracken, Mary; Yu, Jennifer W. – Grantee Submission, 2015
Approximately 80% of youth on the autism spectrum in the U.S. who attend college will attend a 2-year college at some point in their postsecondary education. These community-based colleges are universally-accessible educational institutions which offer both academic and vocational courses and are experienced in teaching diverse learners who may…
Descriptors: Community Colleges, Two Year College Students, Student Characteristics, Autism
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Nagle, Katherine; Pratt-Williams, Jaunelle; Schmidt, Rebecca; Swantek, Cara; Lyulchenko, Marianna; McGhee, Raymond – Grantee Submission, 2016
This is the final external evaluation report prepared by SRI International for the Rural Math Excel Partnership (RMEP) project, an investing in innovation (i3) development project funded by the U.S. Department of Education. Operated by Virginia Advanced Study Strategies, Inc. (VASS), the RMEP project included six rural school districts (LEAs) in…
Descriptors: Rural Schools, Mathematics Education, Family Involvement, Mathematics Teachers