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Russell P. Houpt; Kevin J. Grimm; Aaron T. McLaughlin; Daryl R. Van Tongeren – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Numerous methods exist to determine the optimal number of classes when using latent profile analysis (LPA), but none are consistently correct. Recently, the likelihood incremental percentage per parameter (LI3P) was proposed as a model effect-size measure. To evaluate the LI3P more thoroughly, we simulated 50,000 datasets, manipulating factors…
Descriptors: Structural Equation Models, Profiles, Sample Size, Evaluation Methods
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Liu, Ren; Liu, Haiyan; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2022
Assessments with a large amount of small, similar, or often repetitive tasks are being used in educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch…
Descriptors: Classification, Models, Statistical Distributions, Scores
Shear, Benjamin R.; Reardon, Sean F. – Journal of Educational and Behavioral Statistics, 2021
This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Sample Size
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Nam, Yeji; Hong, Sehee – Educational and Psychological Measurement, 2021
This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…
Descriptors: Probability, Models, Statistical Analysis, Statistical Distributions
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Liqun Yin; Ummugul Bezirhan; Matthias von Davier – International Electronic Journal of Elementary Education, 2025
This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…
Descriptors: Multivariate Analysis, Cutting Scores, Achievement Tests, Foreign Countries
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Shin, Myungho; No, Unkyung; Hong, Sehee – Educational and Psychological Measurement, 2019
The present study aims to compare the robustness under various conditions of latent class analysis mixture modeling approaches that deal with auxiliary distal outcomes. Monte Carlo simulations were employed to test the performance of four approaches recommended by previous simulation studies: maximum likelihood (ML) assuming homoskedasticity…
Descriptors: Robustness (Statistics), Multivariate Analysis, Maximum Likelihood Statistics, Statistical Distributions
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Rakhat, Berikbol; Kuralay, Bekbolatova; Akmaral, Smanova; Zhanar, Nebessayeva; Miyat, Dzhanaev – World Journal on Educational Technology: Current Issues, 2021
The aim of this study was to determine the examination of the researches about the use of technology by fine arts teachers. The study was conducted according to the content and citation analysis model. In this context, Web of Science (WOS) Core Collection indexes were included. In the document scanning in the WOS environment, the keywords 'Fine…
Descriptors: Foreign Countries, Technology Uses in Education, Art Education, Fine Arts
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Boppuru, Prarthap Rudra; K, Ramesha – International Journal of Web-Based Learning and Teaching Technologies, 2019
Social media is the platforms where users communicate, interact, share ideas, career interest, pictures, video, etc. Social media gives an opportunity to analyze the human behavior. Crime analysis using data from social media such as Newsfeeds, Facebook, Twitter, etc., is becoming one of the emerging areas of research for law enforcement…
Descriptors: Social Media, Foreign Countries, Prediction, Law Enforcement
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Schuler, Kathryn D.; Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N. – Language Learning and Development, 2017
Successful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their…
Descriptors: Artificial Languages, Grammar, Classification, Word Frequency
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Gagliardi, Annie; Feldman, Naomi H.; Lidz, Jeffrey – Cognitive Science, 2017
Children acquiring languages with noun classes (grammatical gender) have ample statistical information available that characterizes the distribution of nouns into these classes, but their use of this information to classify novel nouns differs from the predictions made by an optimal Bayesian classifier. We use rational analysis to investigate the…
Descriptors: Children, Statistics, Learning, Bayesian Statistics
Zhou, Daniel Xiaodan – ProQuest LLC, 2013
The ability to classify the political leaning of a large number of articles and items is valuable to both academic research and practical applications. The challenge, though, is not only about developing innovative classification algorithms, which constitutes a "classifier" theme in this thesis, but also about how to define the…
Descriptors: Political Attitudes, Social Systems, Classification, Statistical Distributions
Felder, Valerie – ProQuest LLC, 2013
Micceri (1989) examined the distributional characteristics of 440 large-sample achievement and psychometric measures. All the distributions were found to be nonnormal at alpha = 0.01. Micceri indicated three factors that might contribute to a non-Gaussian error distribution in the population. The first factor is subpopulations within a target…
Descriptors: Special Education, Statistical Distributions, Psychometrics, Data Collection
Imbens, Guido W.; Rubin, Donald B. – Cambridge University Press, 2015
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Descriptors: Causal Models, Statistical Inference, Statistics, Social Sciences
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Bramley, Tom – Research in Mathematics Education, 2017
This study compared models of assessment structure for achieving differentiation across the range of examinee attainment in the General Certificate of Secondary Education (GCSE) examination taken by 16-year-olds in England. The focus was on the "adjacent levels" model, where papers are targeted at three specific non-overlapping ranges of…
Descriptors: Foreign Countries, Mathematics Education, Student Certification, Student Evaluation
Annie E. Casey Foundation, 2016
The Annie E. Casey Foundation's "2016 KIDS COUNT Data Book" finds today's youth--Generation Z--are healthier and completing high school on time despite mounting economic inequality and increasingly unaffordable college tuition. Aided by smart policies and investments in prevention, a record number of teens are making positive choices.…
Descriptors: Child Welfare, Economic Impact, Annual Reports, Well Being
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