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Arel-Bundock, Vincent – Sociological Methods & Research, 2022
Qualitative comparative analysis (QCA) is an influential methodological approach motivated by set theory and boolean logic. QCA proponents have developed algorithms to analyze quantitative data, in a bid to uncover necessary and sufficient conditions where causal relationships are complex, conditional, or asymmetric. This article uses computer…
Descriptors: Comparative Analysis, Qualitative Research, Attribution Theory, Computer Simulation
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Tang, Yang; Cook, Thomas D.; Kisbu-Sakarya, Yasemin – Society for Research on Educational Effectiveness, 2015
Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…
Descriptors: Pretests Posttests, Statistical Bias, Accuracy, Regression (Statistics)
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Sun, Shuyan; Pan, Wei – Journal of Experimental Education, 2013
Regression discontinuity design is an alternative to randomized experiments to make causal inference when random assignment is not possible. This article first presents the formal identification and estimation of regression discontinuity treatment effects in the framework of Rubin's causal model, followed by a thorough literature review of…
Descriptors: Regression (Statistics), Computation, Accuracy, Causal Models
Karabatsos, George; Walker, Stephen G. – Society for Research on Educational Effectiveness, 2011
Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…
Descriptors: Bayesian Statistics, Regression (Statistics), Nonparametric Statistics, Statistical Inference