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Thiem, Alrik – Sociological Methods & Research, 2022
Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal…
Descriptors: Comparative Analysis, Causal Models, Inferences, Risk
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York, Richard – International Journal of Social Research Methodology, 2018
A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless "all" potential confounding factors are included in an analysis (which is unlikely to be…
Descriptors: Inferences, Control Groups, Correlation, Experimental Groups
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Motz, Benjamin A.; Carvalho, Paulo F.; de Leeuw, Joshua R.; Goldstone, Robert L. – Journal of Learning Analytics, 2018
To identify the ways teachers and educational systems can improve learning, researchers need to make causal inferences. Analyses of existing datasets play an important role in detecting causal patterns, but conducting experiments also plays an indispensable role in this research. In this article, we advocate for experiments to be embedded in real…
Descriptors: Causal Models, Statistical Inference, Inferences, Educational Experiments
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Cook, Thomas D.; Steiner, Peter M. – Psychological Methods, 2010
In this article, we note the many ontological, epistemological, and methodological similarities between how Campbell and Rubin conceptualize causation. We then explore 3 differences in their written emphases about individual case matching in observational studies. We contend that (a) Campbell places greater emphasis than Rubin on the special role…
Descriptors: Research Methodology, Pretests Posttests, Data Analysis, Evaluation Methods
Karabatsos, G.; Walker, S.G. – Society for Research on Educational Effectiveness, 2010
Causal inference is central to educational research, where in data analysis the aim is to learn the causal effects of educational treatments on academic achievement, to evaluate educational policies and practice. Compared to a correlational analysis, a causal analysis enables policymakers to make more meaningful statements about the efficacy of…
Descriptors: Bayesian Statistics, Causal Models, Educational Research, Writing Instruction
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Wu, Amery D.; Zumbo, Bruno D. – Social Indicators Research, 2008
Mediation and moderation are two theories for refining and understanding a causal relationship. Empirical investigation of mediators and moderators requires an integrated research design rather than the data analyses driven approach often seen in the literature. This paper described the conceptual foundation, research design, data analysis, as…
Descriptors: Research Design, Investigations, Structural Equation Models, Data Analysis
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Attewell, Paul A.; Lavin, David E.; Domina, Thurston; Levey, Tania – Journal of Higher Education, 2006
Using college transcripts, we separate the effects of remedial coursework from high school preparation. For two-year colleges, taking remedial classes was "not" associated with less academic success. In four-year colleges, there "are" negative effects of remedial coursework, but many minority students who complete a bachelor's…
Descriptors: Minority Groups, Remedial Instruction, Inferences, Literature Reviews