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Mangino, Anthony A.; Bolin, Jocelyn H.; Finch, W. Holmes – Educational and Psychological Measurement, 2023
This study seeks to compare fixed and mixed effects models for the purposes of predictive classification in the presence of multilevel data. The first part of the study utilizes a Monte Carlo simulation to compare fixed and mixed effects logistic regression and random forests. An applied examination of the prediction of student retention in the…
Descriptors: Prediction, Classification, Monte Carlo Methods, Foreign Countries
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Lions, Séverin; Dartnell, Pablo; Toledo, Gabriela; Godoy, María Inés; Córdova, Nora; Jiménez, Daniela; Lemarié, Julie – Educational and Psychological Measurement, 2023
Even though the impact of the position of response options on answers to multiple-choice items has been investigated for decades, it remains debated. Research on this topic is inconclusive, perhaps because too few studies have obtained experimental data from large-sized samples in a real-world context and have manipulated the position of both…
Descriptors: Multiple Choice Tests, Test Items, Item Analysis, Responses
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Liu, Ivy; Suesse, Thomas; Harvey, Samuel; Gu, Peter Yongqi; Fernández, Daniel; Randal, John – Educational and Psychological Measurement, 2023
The Mantel-Haenszel estimator is one of the most popular techniques for measuring differential item functioning (DIF). A generalization of this estimator is applied to the context of DIF to compare items by taking the covariance of odds ratio estimators between dependent items into account. Unlike the Item Response Theory, the method does not rely…
Descriptors: Test Bias, Computation, Statistical Analysis, Achievement Tests
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Rios, Joseph A. – Educational and Psychological Measurement, 2021
Low test-taking effort as a validity threat is common when examinees perceive an assessment context to have minimal personal value. Prior research has shown that in such contexts, subgroups may differ in their effort, which raises two concerns when making subgroup mean comparisons. First, it is unclear how differential effort could influence…
Descriptors: Response Style (Tests), Statistical Analysis, Measurement, Comparative Analysis
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Huang, Hung-Yu – Educational and Psychological Measurement, 2020
In educational assessments and achievement tests, test developers and administrators commonly assume that test-takers attempt all test items with full effort and leave no blank responses with unplanned missing values. However, aberrant response behavior--such as performance decline, dropping out beyond a certain point, and skipping certain items…
Descriptors: Item Response Theory, Response Style (Tests), Test Items, Statistical Analysis
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Liu, Yuan; Hau, Kit-Tai – Educational and Psychological Measurement, 2020
In large-scale low-stake assessment such as the Programme for International Student Assessment (PISA), students may skip items (missingness) which are within their ability to complete. The detection and taking care of these noneffortful responses, as a measure of test-taking motivation, is an important issue in modern psychometric models.…
Descriptors: Response Style (Tests), Motivation, Test Items, Statistical Analysis
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Sachse, Karoline A.; Mahler, Nicole; Pohl, Steffi – Educational and Psychological Measurement, 2019
Mechanisms causing item nonresponses in large-scale assessments are often said to be nonignorable. Parameter estimates can be biased if nonignorable missing data mechanisms are not adequately modeled. In trend analyses, it is plausible for the missing data mechanism and the percentage of missing values to change over time. In this article, we…
Descriptors: International Assessment, Response Style (Tests), Achievement Tests, Foreign Countries
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Sideridis, Georgios D. – Educational and Psychological Measurement, 2016
The purpose of the present studies was to test the hypothesis that the psychometric characteristics of ability scales may be significantly distorted if one accounts for emotional factors during test taking. Specifically, the present studies evaluate the effects of anxiety and motivation on the item difficulties of the Rasch model. In Study 1, the…
Descriptors: Learning Disabilities, Test Validity, Measures (Individuals), Hierarchical Linear Modeling
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Zehner, Fabian; Sälzer, Christine; Goldhammer, Frank – Educational and Psychological Measurement, 2016
Automatic coding of short text responses opens new doors in assessment. We implemented and integrated baseline methods of natural language processing and statistical modelling by means of software components that are available under open licenses. The accuracy of automatic text coding is demonstrated by using data collected in the "Programme…
Descriptors: Educational Assessment, Coding, Automation, Responses
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Mashburn, Andrew J.; Meyer, J. Patrick; Allen, Joseph P.; Pianta, Robert C. – Educational and Psychological Measurement, 2014
Observational methods are increasingly being used in classrooms to evaluate the quality of teaching. Operational procedures for observing teachers are somewhat arbitrary in existing measures and vary across different instruments. To study the effect of different observation procedures on score reliability and validity, we conducted an experimental…
Descriptors: Observation, Teacher Evaluation, Reliability, Validity
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Timmermans, Anneke C.; Snijders, Tom A. B.; Bosker, Roel J. – Educational and Psychological Measurement, 2013
In traditional studies on value-added indicators of educational effectiveness, students are usually treated as belonging to those schools where they took their final examination. However, in practice, students sometimes attend multiple schools and therefore it is questionable whether this assumption of belonging to the last school they attended…
Descriptors: School Effectiveness, Student Mobility, Elementary Schools, Secondary Schools