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Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
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Demir, Suleyman – International Journal of Assessment Tools in Education, 2022
This study aims to compare normality tests in different sample sizes in data with normal distribution under different kurtosis and skewness coefficients obtained simulatively. To this end, firstly, simulative data were produced using the MATLAB program for different skewness/kurtosis coefficients and different sample sizes. The normality analysis…
Descriptors: Sample Size, Comparative Analysis, Computer Software, Evaluation Methods
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Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2022
Power analysis based on the analytical t-test is an important aspect of a research study to determine the sample size required to detect the effect for the comparison of two means. The current paper presents a reader-friendly procedure for carrying out the t-test power analysis using the various R add-on packages. While there is a growing of R…
Descriptors: Programming Languages, Sample Size, Bayesian Statistics, Intervention
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Clare Baek; Tenzin Doleck – Knowledge Management & E-Learning, 2024
We examined how Learning Analytics literature represents participants from diverse societies by comparing the studies published with samples from WEIRD (Western, Industrialized, Rich, Democratic) nations versus non-WEIRD nations. By analyzing the Learning Analytics studies published during 2015-2019 (N = 360), we found that most of the studies…
Descriptors: Learning Analytics, Educational Research, Sample Size, Literature Reviews
Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
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Guler, Gul; Cikrikci, Rahime Nukhet – International Journal of Assessment Tools in Education, 2022
The purpose of this study was to investigate the Type I Error findings and power rates of the methods used to determine dimensionality in unidimensional and bidimensional psychological constructs for various conditions (characteristic of the distribution, sample size, length of the test, and interdimensional correlation) and to examine the joint…
Descriptors: Comparative Analysis, Error of Measurement, Decision Making, Factor Analysis
Isaac M. Opper – Annenberg Institute for School Reform at Brown University, 2021
Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not cause small-sample bias…
Descriptors: Randomized Controlled Trials, Sample Size, Statistical Bias, Artificial Intelligence
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Kalkan, Ömür Kaya; Kelecioglu, Hülya – Educational Sciences: Theory and Practice, 2016
Linear factor analysis models used to examine constructs underlying the responses are not very suitable for dichotomous or polytomous response formats. The associated problems cannot be eliminated by polychoric or tetrachoric correlations in place of the Pearson correlation. Therefore, we considered parameters obtained from the NOHARM and FACTOR…
Descriptors: Sample Size, Nonparametric Statistics, Factor Analysis, Correlation
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Konstantopoulos, Spyros – Practical Assessment, Research & Evaluation, 2009
Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…
Descriptors: Social Science Research, Effect Size, Computation, Tables (Data)
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Kim, Seock-Ho – Educational and Psychological Measurement, 2007
The procedures required to obtain the approximate posterior standard deviations of the parameters in the three commonly used item response models for dichotomous items are described and used to generate values for some common situations. The results were compared with those obtained from maximum likelihood estimation. It is shown that the use of…
Descriptors: Item Response Theory, Computation, Comparative Analysis, Evaluation Methods
Jansen, Hans P. – 1985
The Air Force Occupational Measurement Center conducts task-based occupational surveys of Air Force specialties that include supervisor ratings on recommended training emphasis for entry-level airmen. Priorities are input to the Instructional System Development training model, which guides the development and revision of specialty training…
Descriptors: Cluster Analysis, Computer Software, Evaluation Methods, Factor Analysis
DeJong, William; Wechsler, Henry – 1998
Under the Drug-Free Schools and Campuses Act, institutions of higher education are required to review the effectiveness of their alcohol and drug prevention programs biannually. This guide offers a method for gathering and interpreting student survey data on alcohol-related problems based on the methodology of the College Alcohol Survey developed…
Descriptors: Alcohol Abuse, College Students, Comparative Analysis, Computer Software