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Yi, Zhiyao; Chen, Yi-Hsin; Yin, Yue; Cheng, Ke; Wang, Yan; Nguyen, Diep; Pham, Thanh; Kim, EunSook – Journal of Experimental Education, 2022
A simulation study was conducted to examine the efficacy of nine frequently-used HOV tests, including Levene's tests with squared residuals and with absolute residuals, Brown and Forsythe (BF) test, Bootstrap BF test, O'Brien test, Z-variance test, Box-Scheffé (BS) test, Bartlett test, and Pseudo jackknife test under comprehensive simulation…
Descriptors: Statistical Analysis, Robustness (Statistics), Sampling, Statistical Inference
Yanli Xie – ProQuest LLC, 2022
The purpose of this dissertation is to develop principles and strategies for and identify limitations of multisite cluster randomized trials in the context of partially and fully nested designs. In the first study, I develop principles of estimation, sampling variability, and inference for studies that leverage multisite designs within the context…
Descriptors: Randomized Controlled Trials, Research Design, Computation, Sampling
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Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
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Lee, Hyung Rock; Sung, Jaeyun; Lee, Sunbok – International Journal of Assessment Tools in Education, 2021
Conventional estimators for indirect effects using a difference in coefficients and product of coefficients produce the same results for continuous outcomes. However, for binary outcomes, the difference in coefficient estimator systematically underestimates the indirect effects because of a scaling problem. One solution is to standardize…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Scaling
Anqi Zhao; Peng Ding; Tirthankar Dasgupta – Grantee Submission, 2018
Given two 2-level factors of interest, a 2[superscript 2] split-plot design (a) takes each of the 2 [superscript 2] = 4 possible factorial combinations as a treatment, (b) identifies one factor as `whole-plot,' (c) divides the experimental units into blocks, and (d) assigns the treatments in such away that all units within the same block receive…
Descriptors: Statistical Inference, Computation, Statistical Analysis, Sampling
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Hayden, Robert W. – Journal of Statistics Education, 2019
Recent years have seen increasing interest in incorporating resampling methods into introductory statistics courses and the high school mathematics curriculum. While the use of permutation tests for data from experiments is a step forward, the use of simple bootstrap methods for sampling situations is more problematical. This article demonstrates…
Descriptors: Sampling, Statistical Inference, Introductory Courses, College Mathematics
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Astivia, Oscar L. Olvera; Zumbo, Bruno D. – Practical Assessment, Research & Evaluation, 2019
Within psychology and the social sciences, Ordinary Least Squares (OLS) regression is one of the most popular techniques for data analysis. In order to ensure the inferences from the use of this method are appropriate, several assumptions must be satisfied, including the one of constant error variance (i.e. homoskedasticity). Most of the training…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Statistical Analysis, Error of Measurement
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Wang, Yan; Kim, Eun Sook; Nguyen, Diep Thi; Pham, Thanh Vinh; Chen, Yi-Hsin; Yi, Zhiyao – AERA Online Paper Repository, 2017
The analysis of variance (ANOVA) F test is a commonly used method to test the mean equality among two or more populations. A critical assumption of ANOVA is homogeneity of variance (HOV), that is, the compared groups have equal variances. Although it is encouraged to test HOV as part of the regular ANOVA procedure, the efficacy of the initial HOV…
Descriptors: Statistical Analysis, Error of Measurement, Robustness (Statistics), Sampling
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Cappaert, Kevin J.; Wen, Yao; Chang, Yu-Feng – Measurement: Interdisciplinary Research and Perspectives, 2018
Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Identification
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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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Banjanovic, Erin S.; Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2016
Confidence intervals for effect sizes (CIES) provide readers with an estimate of the strength of a reported statistic as well as the relative precision of the point estimate. These statistics offer more information and context than null hypothesis statistic testing. Although confidence intervals have been recommended by scholars for many years,…
Descriptors: Computation, Statistical Analysis, Effect Size, Sampling
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Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference
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Bai, Haiyan; Sivo, Stephen A.; Pan, Wei; Fan, Xitao – International Journal of Research & Method in Education, 2016
Among the commonly used resampling methods of dealing with small-sample problems, the bootstrap enjoys the widest applications because it often outperforms its counterparts. However, the bootstrap still has limitations when its operations are contemplated. Therefore, the purpose of this study is to examine an alternative, new resampling method…
Descriptors: Sampling, Structural Equation Models, Statistical Inference, Comparative Analysis
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Padilla, Miguel A.; Divers, Jasmin – Educational and Psychological Measurement, 2016
Coefficient omega and alpha are both measures of the composite reliability for a set of items. Unlike coefficient alpha, coefficient omega remains unbiased with congeneric items with uncorrelated errors. Despite this ability, coefficient omega is not as widely used and cited in the literature as coefficient alpha. Reasons for coefficient omega's…
Descriptors: Reliability, Computation, Statistical Analysis, Comparative Analysis
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Paek, Insu – Educational and Psychological Measurement, 2016
The effect of guessing on the point estimate of coefficient alpha has been studied in the literature, but the impact of guessing and its interactions with other test characteristics on the interval estimators for coefficient alpha has not been fully investigated. This study examined the impact of guessing and its interactions with other test…
Descriptors: Guessing (Tests), Computation, Statistical Analysis, Test Length
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