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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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Taylor, John M. – Practical Assessment, Research & Evaluation, 2019
Although frequentist estimators can effectively fit ordinal confirmatory factor analysis (CFA) models, their assumptions are difficult to establish and estimation problems may prohibit their use at times. Consequently, researchers may want to also look to Bayesian analysis to fit their ordinal models. Bayesian methods offer researchers an…
Descriptors: Bayesian Statistics, Factor Analysis, Least Squares Statistics, Error of Measurement
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Jescovitch, Lauren N.; Scott, Emily E.; Cerchiara, Jack A.; Doherty, Jennifer H.; Wenderoth, Mary Pat; Merrill, John E.; Urban-Lurain, Mark; Haudek, Kevin C. – Practical Assessment, Research & Evaluation, 2019
Constructed responses can be used to assess the complexity of student thinking and can be evaluated using rubrics. The two most typical rubric types used are holistic and analytic. Holistic rubrics may be difficult to use with expert-level reasoning that has additive or overlapping language. In an attempt to unpack complexity in holistic rubrics…
Descriptors: Scoring Rubrics, Measurement, Logical Thinking, Scientific Concepts
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Bashkov, Bozhidar M.; Clauser, Jerome C. – Practical Assessment, Research & Evaluation, 2019
Successful testing programs rely on high-quality test items to produce reliable scores and defensible exams. However, determining what statistical screening criteria are most appropriate to support these goals can be daunting. This study describes and demonstrates cost-benefit analysis as an empirical approach to determining appropriate screening…
Descriptors: Test Items, Test Reliability, Evaluation Criteria, Accuracy
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Scott, Paul Wesley – Practical Assessment, Research & Evaluation, 2019
Two approaches to causal inference in the presence of non-random assignment are presented: The Propensity Score approach which pseudo-randomizes by balancing groups on observed propensity to be in treatment, and the Endogenous Treatment Effects approach which utilizes systems of equations to explicitly model selection into treatment. The three…
Descriptors: Causal Models, Statistical Inference, Probability, Scores
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Huebner, Alan; Lucht, Marissa – Practical Assessment, Research & Evaluation, 2019
Generalizability theory is a modern, powerful, and broad framework used to assess the reliability, or dependability, of measurements. While there exist classic works that explain the basic concepts and mathematical foundations of the method, there is currently a lack of resources addressing computational resources for those researchers wishing to…
Descriptors: Generalizability Theory, Test Reliability, Computer Software, Statistical Analysis
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Basileo, Lindsey Devers; Toth, Michael – Practical Assessment, Research & Evaluation, 2019
The purpose of the study is to close the gap in the literature regarding the Marzano Teacher Evaluation Model (MTEM) that lacks large scale empirical investigations to assess the predictability of the model. The study thoroughly reviews the extant literature from all teacher evaluation frameworks, particularly focusing on the large body of…
Descriptors: Teacher Evaluation, Value Added Models, Prediction, Teacher Effectiveness
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Wilhelm, Anne Garrison; Gillespie Rouse, Amy; Jones, Francesca – Practical Assessment, Research & Evaluation, 2018
Although inter-rater reliability is an important aspect of using observational instruments, it has received little theoretical attention. In this article, we offer some guidance for practitioners and consumers of classroom observations so that they can make decisions about inter-rater reliability, both for study design and in the reporting of data…
Descriptors: Interrater Reliability, Measurement, Observation, Educational Research
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Howard, Matt C. – Practical Assessment, Research & Evaluation, 2018
Scale pretests analyze the suitability of individual scale items for further analysis, whether through judging their face validity, wording concerns, and/or other aspects. The current article reviews scale pretests, separated by qualitative and quantitative methods, in order to identify the differences, similarities, and even existence of the…
Descriptors: Pretesting, Measures (Individuals), Test Items, Statistical Analysis
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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
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Dogan, Enis – Practical Assessment, Research & Evaluation, 2018
Several large scale assessments include student, teacher, and school background questionnaires. Results from such questionnaires can be reported for each item separately, or as indices based on aggregation of multiple items into a scale. Interpreting scale scores is not always an easy task though. In disseminating results of achievement tests, one…
Descriptors: Rating Scales, Benchmarking, Questionnaires, Achievement Tests
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Wyse, Adam E. – Practical Assessment, Research & Evaluation, 2018
One common modification to the Angoff standard-setting method is to have panelists round their ratings to the nearest 0.05 or 0.10 instead of 0.01. Several reasons have been offered as to why it may make sense to have panelists round their ratings to the nearest 0.05 or 0.10. In this article, we examine one reason that has been suggested, which is…
Descriptors: Interrater Reliability, Evaluation Criteria, Scoring Formulas, Achievement Rating
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Shear, Benjamin R.; Nordstokke, David W.; Zumbo, Bruno D. – Practical Assessment, Research & Evaluation, 2018
This computer simulation study evaluates the robustness of the nonparametric Levene test of equal variances (Nordstokke & Zumbo, 2010) when sampling from populations with unequal (and unknown) means. Testing for population mean differences when population variances are unknown and possibly unequal is often referred to as the Behrens-Fisher…
Descriptors: Nonparametric Statistics, Computer Simulation, Monte Carlo Methods, Sampling
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Barnard, John J. – Practical Assessment, Research & Evaluation, 2018
Measurement specialists strive to shorten assessment time without compromising precision of scores. Computerized Adaptive Testing (CAT) has rapidly gained ground over the past decades to fulfill this goal. However, parameters for implementation of CATs need to be explored in simulations before implementation so that it can be determined whether…
Descriptors: Computer Assisted Testing, Adaptive Testing, Simulation, Multiple Choice Tests
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Iwatani, Emi – Practical Assessment, Research & Evaluation, 2018
Education researchers are increasingly interested in applying data mining approaches, but to date, there has been no overarching exposition of their methodological advantages and disadvantages to the field. This is partly because the use of data mining in education research is relatively new, so its value and consequences are not yet well…
Descriptors: Data Analysis, Educational Research, Research Problems, Statistics
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