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Green, Samuel B.; Redell, Nickalus; Thompson, Marilyn S.; Levy, Roy – Educational and Psychological Measurement, 2016
Parallel analysis (PA) is a useful empirical tool for assessing the number of factors in exploratory factor analysis. On conceptual and empirical grounds, we argue for a revision to PA that makes it more consistent with hypothesis testing. Using Monte Carlo methods, we evaluated the relative accuracy of the revised PA (R-PA) and traditional PA…
Descriptors: Accuracy, Factor Analysis, Hypothesis Testing, Monte Carlo Methods
Porter, Kristin E. – Journal of Research on Educational Effectiveness, 2018
Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Pan, Tianshu; Yin, Yue – Applied Measurement in Education, 2017
In this article, we propose using the Bayes factors (BF) to evaluate person fit in item response theory models under the framework of Bayesian evaluation of an informative diagnostic hypothesis. We first discuss the theoretical foundation for this application and how to analyze person fit using BF. To demonstrate the feasibility of this approach,…
Descriptors: Bayesian Statistics, Goodness of Fit, Item Response Theory, Monte Carlo Methods
Porter, Kristin E. – Grantee Submission, 2017
Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs) are statistical…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Porter, Kristin E. – MDRC, 2016
In education research and in many other fields, researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple…
Descriptors: Statistical Analysis, Program Effectiveness, Intervention, Hypothesis Testing
Spencer, Bryden – ProQuest LLC, 2016
Value-added models are a class of growth models used in education to assign responsibility for student growth to teachers or schools. For value-added models to be used fairly, sufficient statistical precision is necessary for accurate teacher classification. Previous research indicated precision below practical limits. An alternative approach has…
Descriptors: Monte Carlo Methods, Comparative Analysis, Accuracy, High Stakes Tests
Berkovich, Izhak; Eyal, Ori – Educational Management Administration & Leadership, 2017
The present study aims to examine whether principals' emotional intelligence (specifically, their ability to recognize emotions in others) makes them more effective transformational leaders, measured by the reframing of teachers' emotions. The study uses multisource data from principals and their teachers in 69 randomly sampled primary schools.…
Descriptors: Principals, Transformational Leadership, Administrator Behavior, Administrator Role
Schoemann, Alexander M.; Miller, Patrick; Pornprasertmanit, Sunthud; Wu, Wei – International Journal of Behavioral Development, 2014
Planned missing data designs allow researchers to increase the amount and quality of data collected in a single study. Unfortunately, the effect of planned missing data designs on power is not straightforward. Under certain conditions using a planned missing design will increase power, whereas in other situations using a planned missing design…
Descriptors: Monte Carlo Methods, Simulation, Sample Size, Research Design
Rusconi, Patrice; Marelli, Marco; D'Addario, Marco; Russo, Selena; Cherubini, Paolo – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Evidence evaluation is a crucial process in many human activities, spanning from medical diagnosis to impression formation. The present experiments investigated which, if any, normative model best conforms to people's intuition about the value of the obtained evidence. Psychologists, epistemologists, and philosophers of science have proposed…
Descriptors: Experimental Psychology, Models, Intuition, Evidence
Itang'ata, Mukaria J. J. – ProQuest LLC, 2013
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…
Descriptors: Comparative Analysis, Probability, Statistical Bias, Monte Carlo Methods
Lix, Lisa M.; Sajobi, Tolulope – Psychological Methods, 2010
This study investigates procedures for controlling the familywise error rate (FWR) when testing hypotheses about multiple, correlated outcome variables in repeated measures (RM) designs. A content analysis of RM research articles published in 4 psychology journals revealed that 3 quarters of studies tested hypotheses about 2 or more outcome…
Descriptors: Hypothesis Testing, Correlation, Statistical Analysis, Research Design
Solanas, Antonio; Manolov, Rumen; Sierra, Vicenta – Psicologica: International Journal of Methodology and Experimental Psychology, 2010
In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is…
Descriptors: Computation, Hypothesis Testing, Correlation, Monte Carlo Methods
Finch, Holmes; Habing, Brian – Applied Psychological Measurement, 2007
This Monte Carlo study compares the ability of the parametric bootstrap version of DIMTEST with three goodness-of-fit tests calculated from a fitted NOHARM model to detect violations of the assumption of unidimensionality in testing data. The effectiveness of the procedures was evaluated for different numbers of items, numbers of examinees,…
Descriptors: Guessing (Tests), Testing, Statistics, Monte Carlo Methods

Silver, N. Clayton; Dunlap, William P. – Educational and Psychological Measurement, 1989
A Monte Carlo simulation examined the Type I error rates and power of four tests of the null hypothesis that a correlation matrix equals the identity matrix. The procedure of C. J. Brien and others (1984) was found to be the most powerful test maintaining stable empirical alpha values. (SLD)
Descriptors: Correlation, Hypothesis Testing, Monte Carlo Methods, Power (Statistics)

Mendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1978
Four testing procedures for establishing the number of non-zero population roots in canonical analysis are investigated. Results of a Monte Carlo study indicate that three well-established procedures were effective, and a new procedure designed to correct a supposed flaw in the other procedures was ineffective. (JKS)
Descriptors: Correlation, Hypothesis Testing, Monte Carlo Methods, Multivariate Analysis
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