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Walters, Glenn D. – International Journal of Social Research Methodology, 2019
Identifying mediators in variable chains as part of a causal mediation analysis can shed light on issues of causation, assessment, and intervention. However, coefficients and effect sizes in a causal mediation analysis are nearly always small. This can lead those less familiar with the approach to reject the results of causal mediation analysis.…
Descriptors: Effect Size, Statistical Analysis, Sampling, Statistical Inference
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Showalter, Daniel A.; Mullet, Luke B. – Mid-Western Educational Researcher, 2017
Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…
Descriptors: Educational Research, Selection Criteria, Selection Tools, Bias
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Cox, Bradley E.; McIntosh, Kadian; Reason, Robert D.; Terenzini, Patrick T. – Review of Higher Education, 2014
Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…
Descriptors: Data Analysis, Statistical Inference, Research Problems, Computation
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Chan, Wai – Educational and Psychological Measurement, 2009
A typical question in multiple regression analysis is to determine if a set of predictors gives the same degree of predictor power in two different populations. Olkin and Finn (1995) proposed two asymptotic-based methods for testing the equality of two population squared multiple correlations, [rho][superscript 2][subscript 1] and…
Descriptors: Multiple Regression Analysis, Intervals, Correlation, Computation