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Custer, Michael; Kim, Jongpil – Online Submission, 2023
This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…
Descriptors: Sample Size, Item Response Theory, Test Items, Computation
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Lorah, Julie Ann – AERA Online Paper Repository, 2018
The Bayesian information criterion (BIC) can be useful for model selection within multilevel modeling studies. However, the formula for BIC requires a value for N, which is unclear in multilevel models, since N is observed in at least two levels. The present study uses simulated data to evaluate the rate of false positives and power when using a…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Computation, Statistical Analysis
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Dai, Ting; Du, Yang; Cromley, Jennifer G.; Fechter, Tia M.; Nelson, Frank – AERA Online Paper Repository, 2019
Certain planned-missing designs (e.g., simple-matrix sampling) cause zero covariances between variables not jointly observed, making it impossible to do analyses beyond mean estimations without specialized analyses. We tested a multigroup confirmatory factor analysis (CFA) approach by Cudeck (2000), which obtains a model-estimated…
Descriptors: Factor Analysis, Educational Research, Research Design, Data Analysis
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Pustejovsky, James Eric; Furman, Gleb – AERA Online Paper Repository, 2017
In linear regression models estimated by ordinary least squares, it is often desirable to use hypothesis tests and confidence intervals that remain valid in the presence of heteroskedastic errors. Wald tests based on heteroskedasticity-consistent covariance matrix estimators (HCCMEs, also known as sandwich estimators or simply "robust"…
Descriptors: Hypothesis Testing, Sample Size, Regression (Statistics), Computation
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Huang, Jiajing; Liang, Xinya; Yang, Yanyun – AERA Online Paper Repository, 2017
In Bayesian structural equation modeling (BSEM), prior settings may affect model fit, parameter estimation, and model comparison. This simulation study was to investigate how the priors impact evaluation of relative fit across competing models. The design factors for data generation included sample sizes, factor structures, data distributions, and…
Descriptors: Bayesian Statistics, Structural Equation Models, Goodness of Fit, Sample Size
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Joo, Seang-hwane; Wang, Yan; Ferron, John M. – AERA Online Paper Repository, 2017
Multiple-baseline studies provide meta-analysts the opportunity to compute effect sizes based on either within-series comparisons of treatment phase to baseline phase observations, or time specific between-series comparisons of observations from those that have started treatment to observations of those that are still in baseline. The advantage of…
Descriptors: Meta Analysis, Effect Size, Hierarchical Linear Modeling, Computation
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Inzunsa Cazares, Santiago – North American Chapter of the International Group for the Psychology of Mathematics Education, 2016
This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…
Descriptors: Qualitative Research, College Students, Inferences, Logical Thinking
Custer, Michael – Online Submission, 2015
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
Descriptors: Sample Size, Item Response Theory, Computation, Accuracy
Ware, William B.; Althouse, Linda Akel – 1999
This study was designed to derive the distribution of a test statistic based on normal probability plots. The first purpose was to provide an empirical derivation of the critical values for the Line Test (LT) with an extensive computer simulation. The goal was to develop a test that is sensitive to a wide range of alternative distributions,…
Descriptors: Computation, Computer Simulation, Monte Carlo Methods, Probability
Lambert, Richard; Flowers, Claudia; Sipe, Theresa; Idleman, Lynda – 1997
This paper discusses three software packages that offer unique features and options that greatly simplify the research package for conducting surveys. The first package, EPSILON, from Resource Group, Ltd. of Dallas (Texas) is designed to perform a variety of sample size calculations covering most of the commonly encountered survey research…
Descriptors: Computation, Computer Software, Data Analysis, Integrated Activities
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Cota, Albert A.; And Others – Educational and Psychological Measurement, 1993
Focusing on linear interpolation, an accurate method of implementing parallel analysis, this article contains tables of 95th percentile eigenvalues from random data than can be used with sample sizes of 50 to 500 subjects and between 5 and 50 variables. An empirical example illustrates how to obtain the eigenvalues. (SLD)
Descriptors: Comparative Analysis, Computation, Factor Analysis, Monte Carlo Methods
Daniel, Thomas – 1992
This paper studies statistical procedures used in the "Journal of Research in Music Education" (JRME) over a 5-year period (1987 through 1991). The results are compared with those of L. D. Goodwin and W. L. Goodwin (1985) concerning the "American Educational Research Journal" for the same period. In all, 78 quantitative and 31…
Descriptors: Computation, Computer Software, Educational Research, Educational Trends