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Shadish, William; Hedges, Larry; Pustejovsky, James; Rindskopf, David – Society for Research on Educational Effectiveness, 2012
Over the last 10 years, numerous authors have proposed effect size estimators for single-case designs. None, however, has been shown to be equivalent to the usual between-groups standardized mean difference statistic, sometimes called d. The present paper remedies that omission. Most effect size estimators for single-case designs use the…
Descriptors: Effect Size, Experiments, Sample Size, Comparative Analysis
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Watson, Jane; Chance, Beth – Australian Senior Mathematics Journal, 2012
Formal inference, which makes theoretical assumptions about distributions and applies hypothesis testing procedures with null and alternative hypotheses, is notoriously difficult for tertiary students to master. The debate about whether this content should appear in Years 11 and 12 of the "Australian Curriculum: Mathematics" has gone on…
Descriptors: Foreign Countries, Research Methodology, Sampling, Statistical Inference
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Trafimow, David; MacDonald, Justin A.; Rice, Stephen; Clason, Dennis L. – Psychological Methods, 2010
Largely due to dissatisfaction with the standard null hypothesis significance testing procedure, researchers have begun to consider alternatives. For example, Killeen (2005a) has argued that researchers should calculate p[subscript rep] that is purported to indicate the probability that, if the experiment in question were replicated, the obtained…
Descriptors: Probability, Replication (Evaluation), Statistics, Comparative Analysis
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Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
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Savalei, Victoria – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Incomplete nonnormal data are common occurrences in applied research. Although these 2 problems are often dealt with separately by methodologists, they often cooccur. Very little has been written about statistics appropriate for evaluating models with such data. This article extends several existing statistics for complete nonnormal data to…
Descriptors: Sample Size, Statistics, Data, Monte Carlo Methods
Navarrete-Alvarez, Esteban; Rosales-Moreno, Maria Jesus; Huete-Morales, Maria Dolores – Online Submission, 2010
Statistics teaching should not be carried out in the same way for all kinds of university students. Instead, teaching statistics should take into account the different fields of study that students have chosen. For example, students of sciences or engineering have different interests and backgrounds compared to students of any social or juridical…
Descriptors: Academic Achievement, Statistics, Labor, Teaching Methods
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Henson, James M.; Reise, Steven P.; Kim, Kevin H. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…
Descriptors: Statistics, Structural Equation Models, Comparative Analysis, Sample Size
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Strang, Kenneth David – Practical Assessment, Research & Evaluation, 2009
This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…
Descriptors: Multicultural Education, Computer Software, Multiple Regression Analysis, Multidimensional Scaling
Porter, Andrew C.; McSweeney, Maryellen – 1974
A Monte Carlo technique was used to investigate the small sample goodness of fit and statistical power of several nonparametric tests and their parametric analogues when applied to data which violate parametric assumptions. The motivation was to facilitate choice among three designs, simple random assignment with and without a concomitant variable…
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Goodness of Fit