Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 5 |
Since 2016 (last 10 years) | 7 |
Since 2006 (last 20 years) | 10 |
Descriptor
Classification | 12 |
Error of Measurement | 12 |
Monte Carlo Methods | 12 |
Accuracy | 5 |
Regression (Statistics) | 5 |
Comparative Analysis | 4 |
Item Analysis | 4 |
Statistical Bias | 4 |
Evaluation Methods | 3 |
Item Response Theory | 3 |
Sample Size | 3 |
More ▼ |
Source
Journal of Experimental… | 5 |
Applied Measurement in… | 1 |
Educational and Psychological… | 1 |
Journal of Educational… | 1 |
Measurement:… | 1 |
ProQuest LLC | 1 |
Structural Equation Modeling:… | 1 |
Author
Dardick, William | 2 |
Weiss, Brandi A. | 2 |
Ben Kelcey | 1 |
Jiao, Hong | 1 |
Jin, Ying | 1 |
Kamata, Akihito | 1 |
Koehly, Laura M. | 1 |
Lei, Pui-Wa | 1 |
Liu, Yixing | 1 |
Mark H. C. Lai | 1 |
Moore, Matthew | 1 |
More ▼ |
Publication Type
Reports - Research | 11 |
Journal Articles | 10 |
Dissertations/Theses -… | 1 |
Education Level
Grade 8 | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Secondary Education | 1 |
Audience
Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
National Assessment of… | 1 |
Program for International… | 1 |
Progress in International… | 1 |
Trends in International… | 1 |
What Works Clearinghouse Rating
Najera, Hector – Measurement: Interdisciplinary Research and Perspectives, 2023
Measurement error affects the quality of population orderings of an index and, hence, increases the misclassification of the poor and the non-poor groups and affects statistical inferences from binary regression models. Hence, the conclusions about the extent, profile, and distribution of poverty are likely to be misleading. However, the size and…
Descriptors: Poverty, Error of Measurement, Classification, Statistical Inference
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Weiss, Brandi A.; Dardick, William – Journal of Experimental Education, 2021
Classification measures and entropy variants can be used as indicators of model fit for logistic regression. These measures rely on a cut-point, "c," to determine predicted group membership. While recommendations exist for determining the location of the cut-point, these methods are primarily anecdotal. The current study used Monte Carlo…
Descriptors: Cutting Scores, Regression (Statistics), Classification, Monte Carlo Methods
Weiss, Brandi A.; Dardick, William – Journal of Experimental Education, 2020
Researchers are often reluctant to rely on classification rates because a model with favorable classification rates but poor separation may not replicate well. In comparison, entropy captures information about borderline cases unlikely to generalize to the population. In logistic regression, the correctness of predicted group membership is known,…
Descriptors: Classification, Regression (Statistics), Goodness of Fit, Monte Carlo Methods
Liu, Yixing; Thompson, Marilyn S. – Journal of Experimental Education, 2022
A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data…
Descriptors: Comparative Analysis, Item Analysis, Sample Size, Error of Measurement
Paulsen, Justin; Valdivia, Dubravka Svetina – Journal of Experimental Education, 2022
Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using…
Descriptors: Psychometrics, Classification, Teaching Methods, Learning Processes
Nugent, William Robert; Moore, Matthew; Story, Erin – Educational and Psychological Measurement, 2015
The standardized mean difference (SMD) is perhaps the most important meta-analytic effect size. It is typically used to represent the difference between treatment and control population means in treatment efficacy research. It is also used to represent differences between populations with different characteristics, such as persons who are…
Descriptors: Error of Measurement, Error Correction, Predictor Variables, Monte Carlo Methods
Spencer, Bryden – ProQuest LLC, 2016
Value-added models are a class of growth models used in education to assign responsibility for student growth to teachers or schools. For value-added models to be used fairly, sufficient statistical precision is necessary for accurate teacher classification. Previous research indicated precision below practical limits. An alternative approach has…
Descriptors: Monte Carlo Methods, Comparative Analysis, Accuracy, High Stakes Tests
Rutkowski, Leslie – Applied Measurement in Education, 2014
Large-scale assessment programs such as the National Assessment of Educational Progress (NAEP), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA) use a sophisticated assessment administration design called matrix sampling that minimizes the testing burden on individual…
Descriptors: Measurement, Testing, Item Sampling, Computation
Jiao, Hong; Kamata, Akihito; Wang, Shudong; Jin, Ying – Journal of Educational Measurement, 2012
The applications of item response theory (IRT) models assume local item independence and that examinees are independent of each other. When a representative sample for psychometric analysis is selected using a cluster sampling method in a testlet-based assessment, both local item dependence and local person dependence are likely to be induced.…
Descriptors: Item Response Theory, Test Items, Markov Processes, Monte Carlo Methods
Ziomek, Robert L.; Szymczuk, Mike – 1983
In order to evaluate standard setting procedures, apart from the more commonly applied approach of simply comparing the derived standards or failure rates across various techniques, this study investigated the errors of classification associated with the contrasting groups procedures. Monte Carlo simulations were employed to produce…
Descriptors: Classification, Computer Simulation, Error of Measurement, Evaluation Methods
Lei, Pui-Wa; Koehly, Laura M. – Journal of Experimental Education, 2003
Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…
Descriptors: Monte Carlo Methods, Classification, Discriminant Analysis, Regression (Statistics)