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Thomas Cook; Mansi Wadhwa; Jingwen Zheng – Society for Research on Educational Effectiveness, 2023
Context: A perennial problem in applied statistics is the inability to justify strong claims about cause-and-effect relationships without full knowledge of the mechanism determining selection into treatment. Few research designs other than the well-implemented random assignment study meet this requirement. Researchers have proposed partial…
Descriptors: Observation, Research Design, Causal Models, Computation
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Draper, David – Journal of Educational and Behavioral Statistics, 1995
The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)
Descriptors: Causal Models, Comparative Analysis, Markov Processes, Maximum Likelihood Statistics