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Charlotte Z. Mann; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2025
Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…
Descriptors: Causal Models, Statistical Analysis, Privacy, Risk
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Pfannkuch, Maxine; Arnold, Pip; Wild, Chris J. – Educational Studies in Mathematics, 2015
Currently, instruction pays little attention to the development of students' sampling variability reasoning in relation to statistical inference. In this paper, we briefly discuss the especially designed sampling variability learning experiences students aged about 15 engaged in as part of a research project. We examine assessment and…
Descriptors: Statistical Inference, Statistical Analysis, Sampling, Interviews
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Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer – Journal of Educational and Behavioral Statistics, 2013
Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…
Descriptors: Computation, Regression (Statistics), Comparative Analysis, Models
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Bass, Roger F. – Psychology in the Schools, 1987
Evaluates arguments concerning the generality and statistical analysis of single-subject data. Considers the role of philosophy of science in evaluating research methodology. Single-subject data have special relevance for psychologists and educators who focus on the individual but statistical techniques for analyzing data have numerous…
Descriptors: Data Interpretation, Generalizability Theory, Generalization, Philosophy