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Ben-Michael, Eli; Feller, Avi; Rothstein, Jesse – Grantee Submission, 2021
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The "synthetic control" is a weighted average of control units that balances the treated unit's pre-treatment outcomes and other covariates as closely as possible. A critical feature of the original…
Descriptors: Evaluation Methods, Comparative Analysis, Regression (Statistics), Computation
Hughes, Katherine L.; Miller, Trey; Reese, Kelly – Grantee Submission, 2021
This report from the Career and Technical Education (CTE) Research Network Lead team provides final results from an evaluability assessment of CTE programs that feasibly could be evaluated using a rigorous experimental design. Evaluability assessments (also called feasibility studies) are used in education and other fields, such as international…
Descriptors: Program Evaluation, Vocational Education, Evaluation Methods, Educational Research
Geldhof, G. John; Anthony, Katherine P.; Selig, James P.; Mendez-Luck, Carolyn A. – International Journal of Behavioral Development, 2018
The existence of several accessible sources has led to a proliferation of mediation models in the applied research literature. Most of these sources assume endogenous variables (e.g., M, and Y) have normally distributed residuals, precluding models of binary and/or count data. Although a growing body of literature has expanded mediation models to…
Descriptors: Regression (Statistics), Statistical Analysis, Evaluation Methods, Correlation
Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Cimpian, Joseph R. – Journal of Research on Educational Effectiveness, 2017
A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…
Descriptors: Regression (Statistics), Intervention, Quasiexperimental Design, Simulation
Kim, Yongnam; Steiner, Peter – Educational Psychologist, 2016
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
Descriptors: Quasiexperimental Design, Causal Models, Statistical Inference, Randomized Controlled Trials
Cohen, Ayala; Nahum-Shani, Inbal; Doveh, Etti – Multivariate Behavioral Research, 2010
In their seminal paper, Edwards and Parry (1993) presented the polynomial regression as a better alternative to applying difference score in the study of congruence. Although this method is increasingly applied in congruence research, its complexity relative to other methods for assessing congruence (e.g., difference score methods) was one of the…
Descriptors: Behavioral Sciences, Evaluation Methods, Social Sciences, Social Support Groups
Overall, John E.; Tonidandel, Scott – Multivariate Behavioral Research, 2010
A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…
Descriptors: Monte Carlo Methods, Statistical Significance, Correlation, Depression (Psychology)

Campbell, Donald T. – Evaluation and Program Planning, 1996
Regression artifacts are a source of mistaken causal inference in inferences based on time-series data and from longitudinal studies. These artifacts are illustrated, and it is noted that their magnitude is computable (and distinguishable from genuine effects) if the autocorrelation patterns for various lags is known. (SLD)
Descriptors: Causal Models, Evaluation Methods, Longitudinal Studies, Regression (Statistics)
McCaffrey, Daniel F.; Ridgeway, Greg; Morral, Andrew R. – Psychological Methods, 2004
Causal effect modeling with naturalistic rather than experimental data is challenging. In observational studies participants in different treatment conditions may also differ on pretreatment characteristics that influence outcomes. Propensity score methods can theoretically eliminate these confounds for all observed covariates, but accurate…
Descriptors: Substance Abuse, Causal Models, Adolescents, Statistical Analysis
Madhere, Serge – 1986
One of the most appropriate quasiexperimental approaches to compensatory education is the regression-discontinuity design. However, it remains underutilized, in part because of the need to clarify the link between the mathematical model and administrative decision-making. This paper explains the derivation of a program efficiency index congruent…
Descriptors: Compensatory Education, Cutting Scores, Effect Size, Elementary Education