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Tugay Kaçak; Abdullah Faruk Kiliç – International Journal of Assessment Tools in Education, 2025
Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…
Descriptors: Factor Analysis, Monte Carlo Methods, Mathematical Models, Sample Size
Cuhadar, Ismail – Measurement: Interdisciplinary Research and Perspectives, 2022
In practice, some test items may display misfit at the upper-asymptote of item characteristic curve due to distraction, anxiety, or carelessness by the test takers (i.e., the slipping effect). The conventional item response theory (IRT) models do not take the slipping effect into consideration, which may violate the model fit assumption in IRT.…
Descriptors: Sample Size, Item Response Theory, Test Items, Mathematical Models
Bakbergenuly, Ilyas; Hoaglin, David C.; Kulinskaya, Elena – Research Synthesis Methods, 2020
In random-effects meta-analysis the between-study variance ([tau][superscript 2]) has a key role in assessing heterogeneity of study-level estimates and combining them to estimate an overall effect. For odds ratios the most common methods suffer from bias in estimating [tau][superscript 2] and the overall effect and produce confidence intervals…
Descriptors: Meta Analysis, Statistical Bias, Intervals, Sample Size
Sarkar, Jyotirmoy; Rashid, Mamunur – Educational Research Quarterly, 2017
The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…
Descriptors: Sample Size, Sampling, Visualization, Geometric Concepts
Braham, Hana Manor; Ben-Zvi, Dani – Statistics Education Research Journal, 2017
A fundamental aspect of statistical inference is representation of real-world data using statistical models. This article analyzes students' articulations of statistical models and modeling during their first steps in making informal statistical inferences. An integrated modeling approach (IMA) was designed and implemented to help students…
Descriptors: Foreign Countries, Elementary School Students, Statistical Inference, Mathematical Models
Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
Brubacher, Sonja P.; Roberts, Kim P.; Powell, Martine – Developmental Psychology, 2012
Children (N = 157) 4 to 8 years old participated 1 time (single) or 4 times (repeated) in an interactive event. Across each condition, half were questioned a week later about the only or a specific occurrence of the event ("depth first") and then about what usually happens. Half were prompted in the reverse order ("breadth first"). Children with…
Descriptors: Sample Size, Mathematical Models, Prediction, Regression (Statistics)
Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models
Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning – Journal of Educational and Behavioral Statistics, 2012
The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…
Descriptors: Structural Equation Models, Goodness of Fit, Geometric Concepts, Algebra
Ray, Darrell L. – American Biology Teacher, 2013
Students often enter biology programs deficient in the math and computational skills that would enhance their attainment of a deeper understanding of the discipline. To address some of these concerns, I developed a series of spreadsheet simulation exercises that focus on some of the mathematical foundations of scientific inquiry and the benefits…
Descriptors: Science Instruction, Mathematics Skills, Educational Technology, Spreadsheets
Peer reviewedMillsap, Roger E.; And Others – Educational and Psychological Measurement, 1990
Sixteen tables are presented for critical values of the larger of two sample correlation coefficients from two independent samples, given the sample size and the value of the smaller correlation. These tables allow quick assessment of significance without requiring calculation of the test statistic. (SLD)
Descriptors: Correlation, Mathematical Models, Sample Size, Statistical Significance
Peer reviewedHutchinson, Susan R. – Journal of Experimental Education, 1998
The problem of chance model modifications under varying levels of sample size, model size, and severity of misspecification in confirmatory factor analysis models was examined through Monte Carlo simulations. Findings suggest that practitioners should exercise caution when interpreting modified models unless sample size is quite large. (SLD)
Descriptors: Change, Mathematical Models, Monte Carlo Methods, Sample Size
Peer reviewedLudlow, Larry H. – Educational and Psychological Measurement, 1987
In the process of fitting a quantitative synthesis model, the assumption of homogeneous effect size variation is assessed via omnibus test statistics. Graphical representations of data on techniques for teaching composition skills are used to help determine the extent to which sample estimates deviate from modeled population estimates. (TJH)
Descriptors: Graphs, Mathematical Models, Sample Size, Statistical Analysis
Peer reviewedGibbons, Jean D.; Chakraborti, S. – Journal of Experimental Education, 1991
A simulation study compared the performance of the Mann-Whitney "U" test, Student's "t" test, and the alternate (separate variance) "t" test for two mutually independent random samples from normal distributions, with both one-tailed and two-tailed alternatives. Type I error probabilities were computed with equal and…
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Mathematical Models
Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2007
The impact of outliers on Cronbach's coefficient [alpha] has not been documented in the psychometric or statistical literature. This is an important gap because coefficient [alpha] is the most widely used measurement statistic in all of the social, educational, and health sciences. The impact of outliers on coefficient [alpha] is investigated for…
Descriptors: Psychometrics, Computation, Reliability, Monte Carlo Methods
Peer reviewedWilcox, Rand R. – Journal of Educational Statistics, 1984
Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)
Descriptors: Hypothesis Testing, Mathematical Models, Power (Statistics), Probability

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