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Rustam, Ahmad; Naga, Dali Santun; Supriyati, Yetti – International Journal of Education and Literacy Studies, 2019
Detection of differential item functioning (DIF) is needed in the development of tests to obtain useful items. The Mantel-Haenszel method and standardization are tools for DIF detection based on classical theory assumptions. The study was conducted to highlight the sensitivity and accuracy between the Mantel-Haenszel method and the standardization…
Descriptors: Statistical Analysis, Test Bias, Accuracy, Multiple Choice Tests
Guskey, Thomas R. – NASSP Bulletin, 2019
School leaders today are making important decisions regarding education innovations based on published average effect sizes, even though few understand exactly how effect sizes are calculated or what they mean. This article explains how average effect sizes are determined in meta-analyses and the importance of including measures of variability…
Descriptors: Effect Size, Educational Innovation, Meta Analysis, Statistical Distributions
Raykov, Tenko; Marcoulides, George A.; Harrison, Michael – Measurement: Interdisciplinary Research and Perspectives, 2019
Utilizing the perspective of finite mixture modeling, this note considers whether a finding of a plausible one-parameter logistic model could be spurious for a population with substantial unobserved heterogeneity. A theoretically and empirically important setting is discussed involving the mixture of two latent classes, with the less restrictive…
Descriptors: Models, Evaluation Methods, Social Science Research, Statistical Analysis
Brydges, Christopher R.; Gaeta, Laura – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Null hypothesis significance testing is commonly used in audiology research to determine the presence of an effect. Knowledge of study outcomes, including nonsignificant findings, is important for evidence-based practice. Nonsignificant "p" values obtained from null hypothesis significance testing cannot differentiate between…
Descriptors: Bayesian Statistics, Audiology, Hypothesis Testing, Statistical Significance
Raykov, Tenko; Marcoulides, George A.; Harrison, Michael; Menold, Natalja – Educational and Psychological Measurement, 2019
This note confronts the common use of a single coefficient alpha as an index informing about reliability of a multicomponent measurement instrument in a heterogeneous population. Two or more alpha coefficients could instead be meaningfully associated with a given instrument in finite mixture settings, and this may be increasingly more likely the…
Descriptors: Statistical Analysis, Test Reliability, Measures (Individuals), Computation
Shieh, Gwowen – Journal of Experimental Education, 2019
The analysis of covariance (ANCOVA) is a useful statistical procedure that incorporates covariate features into the adjustment of treatment effects. The consequences of omitted prognostic covariates on the statistical inferences of ANCOVA are well documented in the literature. However, the corresponding influence on sample-size calculations for…
Descriptors: Sample Size, Statistical Analysis, Computation, Accuracy
Trafimow, David; Wang, Tonghui; Wang, Cong – Educational and Psychological Measurement, 2019
Two recent publications in "Educational and Psychological Measurement" advocated that researchers consider using the a priori procedure. According to this procedure, the researcher specifies, prior to data collection, how close she wishes her sample mean(s) to be to the corresponding population mean(s), and the desired probability of…
Descriptors: Statistical Distributions, Sample Size, Equations (Mathematics), Statistical Analysis
Sülkü, Seher Nur; Koçak, Deniz – International Journal of Assessment Tools in Education, 2019
Performance evaluation functions as an essential tool for decision makers in the field of measuring and assessing the performance under the multiple evaluation criteria aspect of the systems such as management, economy, and education system. Besides, academic performance evaluation is one of the critical issues in higher institution of learning.…
Descriptors: College Students, Student Evaluation, Evaluation Criteria, Statistical Analysis
Pentimonti, J.; Petscher, Y.; Stanley, C. – National Center on Improving Literacy, 2019
Sample representativeness is an important piece to consider when evaluating the quality of a screening assessment. If you are trying to determine whether or not the screening tool accurately measures children's skills, you want to ensure that the sample that is used to validate the tool is representative of your population of interest.
Descriptors: Sampling, Screening Tests, Measurement, Test Validity
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2019
According to Wollack and Schoenig (2018), score differencing is one of six types of statistical methods used to detect test fraud. In this paper, we suggested the use of Bayes factors (e.g., Kass & Raftery, 1995) for score differencing. A simulation study shows that the suggested approach performs slightly better than an existing frequentist…
Descriptors: Cheating, Deception, Statistical Analysis, Bayesian Statistics
Angela N. Mabry – ProQuest LLC, 2024
With increased pressure for schools to demonstrate college and career readiness, it is crucial to explore the roles and activities of school counselors, the preservice training they receive, and how those college and career readiness concepts are integrated into their roles. The research questions were (1) What are the current roles and activities…
Descriptors: Middle Schools, High Schools, School Counselors, Career Readiness
Rebecca Burtenshaw; Merrilyn Goos – Mathematics Education Research Group of Australasia, 2024
This position paper examines the phenomenon of the McNamara Fallacy to analyse flawed conceptions of "success" in mathematics learning, normalised assessment structures and their implications for mathematics education. The established presence of the McNamara Fallacy and the ramifications of this statistical fallacy provide a foundation…
Descriptors: Criticism, Misconceptions, Mathematics Education, Success
Stephanie D'Costa; Stephanie Grant; Tara Kulkarni; Adrianna Crossing; Miranda Zahn; Marie L. Tanaka – School Psychology International, 2024
School psychology has heavily relied on quantitative methodology to create and sustain our knowledge of best practices regarding academic, behavioral, and mental health outcomes for students. Nevertheless, underlying assumptions of the neutrality of quantitative data have obfuscated how school psychology research has perpetuated oppressive…
Descriptors: School Psychology, Criticism, Educational Research, Statistical Analysis
Pooja Rana; Mithilesh Kumar Dubey; Lovi Raj Gupta; Amit Kumar Thakur – Interactive Learning Environments, 2024
In recent years, the system of student learning and academic emotions has been taken seriously to re-engineer the teaching-learning process at all levels of education. This research paper considers both aspects of assessing the translation of knowledge i.e. qualitative and quantitative. In the current scenario, quantitative and qualitative…
Descriptors: Educational Assessment, Outcomes of Education, Models, Evaluation Methods
Seyda Ince Sezer; Mehmet Diyaddin Yasar – Science Insights Education Frontiers, 2024
The purpose of this research is to identify the situation through content analysis of scale development studies conducted by Turkish researchers in the field of preschool education. Thus, the overall trend of scale development research in preschool education was established. This research is a document analysis study. The documents studied are…
Descriptors: Foreign Countries, Preschool Education, Preschool Teachers, Measures (Individuals)