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Dahlia K. Remler; Gregg G. Van Ryzin – American Journal of Evaluation, 2025
This article reviews the origins and use of the terms quasi-experiment and natural experiment. It demonstrates how the terms conflate whether variation in the independent variable of interest falls short of random with whether researchers find, rather than intervene to create, that variation. Using the lens of assignment--the process driving…
Descriptors: Quasiexperimental Design, Research Design, Experiments, Predictor Variables
Yongtian Cheng; K. V. Petrides – Educational and Psychological Measurement, 2025
Psychologists are emphasizing the importance of predictive conclusions. Machine learning methods, such as supervised neural networks, have been used in psychological studies as they naturally fit prediction tasks. However, we are concerned about whether neural networks fitted with random datasets (i.e., datasets where there is no relationship…
Descriptors: Psychological Studies, Artificial Intelligence, Cognitive Processes, Predictive Validity
Myoung-jae Lee; Goeun Lee; Jin-young Choi – Sociological Methods & Research, 2025
A linear model is often used to find the effect of a binary treatment D on a noncontinuous outcome Y with covariates X. Particularly, a binary Y gives the popular "linear probability model (LPM)," but the linear model is untenable if X contains a continuous regressor. This raises the question: what kind of treatment effect does the…
Descriptors: Probability, Least Squares Statistics, Regression (Statistics), Causal Models