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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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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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Williams, Matt N.; Gomez Grajales, Carlos Alberto; Kurkiewicz, Dason – Practical Assessment, Research & Evaluation, 2013
In 2002, an article entitled "Four assumptions of multiple regression that researchers should always test" by Osborne and Waters was published in "PARE." This article has gone on to be viewed more than 275,000 times (as of August 2013), and it is one of the first results displayed in a Google search for "regression…
Descriptors: Multiple Regression Analysis, Misconceptions, Reader Response, Predictor Variables
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Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
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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