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Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
Kogar, Hakan – Journal of Education and Learning, 2018
The aim of the present research study was to compare the findings from the nonparametric MSA, DIMTEST and DETECT and the parametric dimensionality determining methods in various simulation conditions by utilizing exploratory and confirmatory methods. For this purpose, various simulation conditions were established based on number of dimensions,…
Descriptors: Evaluation Methods, Nonparametric Statistics, Statistical Analysis, Factor Analysis
Nordstokke, David W.; Colp, S. Mitchell – Practical Assessment, Research & Evaluation, 2018
Often, when testing for shift in location, researchers will utilize nonparametric statistical tests in place of their parametric counterparts when there is evidence or belief that the assumptions of the parametric test are not met (i.e., normally distributed dependent variables). An underlying and often unattended to assumption of nonparametric…
Descriptors: Nonparametric Statistics, Statistical Analysis, Monte Carlo Methods, Sample Size
Qiu, Yuxi; Huggins-Manley, Anne Corinne – Educational and Psychological Measurement, 2019
This study aimed to assess the accuracy of the empirical item characteristic curve (EICC) preequating method given the presence of test speededness. The simulation design of this study considered the proportion of speededness, speededness point, speededness rate, proportion of missing on speeded items, sample size, and test length. After crossing…
Descriptors: Accuracy, Equated Scores, Test Items, Nonparametric Statistics
Jinjin Huang – ProQuest LLC, 2020
Measurement invariance is crucial for an effective and valid measure of a construct. Invariance holds when the latent trait varies consistently across subgroups; in other words, the mean differences among subgroups are only due to true latent ability differences. Differential item functioning (DIF) occurs when measurement invariance is violated.…
Descriptors: Robustness (Statistics), Item Response Theory, Test Items, Item Analysis
Svetina, Dubravka; Levy, Roy – Journal of Experimental Education, 2016
This study investigated the effect of complex structure on dimensionality assessment in compensatory multidimensional item response models using DETECT- and NOHARM-based methods. The performance was evaluated via the accuracy of identifying the correct number of dimensions and the ability to accurately recover item groupings using a simple…
Descriptors: Item Response Theory, Accuracy, Correlation, Sample Size
Beasley, T. Mark – Journal of Experimental Education, 2014
Increasing the correlation between the independent variable and the mediator ("a" coefficient) increases the effect size ("ab") for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation caused by…
Descriptors: Statistical Analysis, Effect Size, Nonparametric Statistics, Statistical Inference
Meyer, J.
Patrick; Seaman, Michael A. – Journal of Experimental Education, 2013
The authors generated exact probability distributions for sample sizes up to 35 in each of three groups ("n" less than or equal to 105) and up to 10 in each of four groups ("n" less than or equal to 40). They compared the exact distributions to the chi-square, gamma, and beta approximations. The beta approximation was best in…
Descriptors: Statistical Analysis, Statistical Distributions, Sample Size, Probability
Keller, Bryan – Psychometrika, 2012
Randomization tests are often recommended when parametric assumptions may be violated because they require no distributional or random sampling assumptions in order to be valid. In addition to being exact, a randomization test may also be more powerful than its parametric counterpart. This was demonstrated in a simulation study which examined the…
Descriptors: Statistical Analysis, Nonparametric Statistics, Simulation, Sampling
Socha, Alan; DeMars, Christine E.; Zilberberg, Anna; Phan, Ha – International Journal of Testing, 2015
The Mantel-Haenszel (MH) procedure is commonly used to detect items that function differentially for groups of examinees from various demographic and linguistic backgrounds--for example, in international assessments. As in some other DIF methods, the total score is used to match examinees on ability. In thin matching, each of the total score…
Descriptors: Test Items, Educational Testing, Evaluation Methods, Ability Grouping
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
Törmänen, Juha; Hämäläinen, Raimo P.; Saarinen, Esa – Learning Organization, 2016
Purpose: Systems intelligence (SI) (Saarinen and Hämäläinen, 2004) is a construct defined as a person's ability to act intelligently within complex systems involving interaction and feedback. SI relates to our ability to act in systems and reason about systems to adaptively carry out productive actions within and with respect to systems such as…
Descriptors: Emotional Intelligence, Factor Analysis, Questionnaires, Sample Size
Lindstromberg, Seth – Language Teaching Research, 2016
This article reviews all (quasi)experimental studies appearing in the first 19 volumes (1997-2015) of "Language Teaching Research" (LTR). Specifically, it provides an overview of how statistical analyses were conducted in these studies and of how the analyses were reported. The overall conclusion is that there has been a tight adherence…
Descriptors: Meta Analysis, Second Language Learning, Second Language Instruction, Guidelines
Graham, Deborah J. – ProQuest LLC, 2016
This nonexperimental quantitative correlation study examined relationships between select special education and standardized testing variables for a purposive homogeneous sample of Arizona secondary school districts with Native American populations, and the archival records for students with disabilities postsecondary outcomes between 2012 and…
Descriptors: Correlation, Secondary Education, Postsecondary Education, American Indian Students
Nandakumar, Ratna; Yu, Feng; Zhang, Yanwei – Applied Psychological Measurement, 2011
DETECT is a nonparametric methodology to identify the dimensional structure underlying test data. The associated DETECT index, "D[subscript max]," denotes the degree of multidimensionality in data. Conditional covariances (CCOV) are the building blocks of this index. In specifying population CCOVs, the latent test composite [theta][subscript TT]…
Descriptors: Nonparametric Statistics, Statistical Analysis, Tests, Data
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