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Sideridis, Georgios D.; Jaffari, Fathima – Measurement and Evaluation in Counseling and Development, 2022
The present study describes an R function that implements six corrective procedures developed by Bartlett, Swain, and Yuan in the correction of 21 statistics associated with the omnibus Chi-square test, the residuals, or fit indices in confirmatory factor analysis (CFA) and structural equation modeling (SEM).
Descriptors: Statistical Analysis, Goodness of Fit, Factor Analysis, Structural Equation Models
Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming – Educational and Psychological Measurement, 2015
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…
Descriptors: Structural Equation Models, Statistical Analysis, Monte Carlo Methods, Computation
Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
Starns, Jeffrey J.; Ma, Qiuli – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
The two-high-threshold (2HT) model of recognition memory assumes that people make memory errors because they fail to retrieve information from memory and make a guess, whereas the continuous unequal-variance (UV) model and the low-threshold (LT) model assume that people make memory errors because they retrieve misleading information from memory.…
Descriptors: Guessing (Tests), Recognition (Psychology), Memory, Tests
Denby, Thomas; Schecter, Jeffrey; Arn, Sean; Dimov, Svetlin; Goldrick, Matthew – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Phonotactics--constraints on the position and combination of speech sounds within syllables--are subject to statistical differences that gradiently affect speaker and listener behavior (e.g., Vitevitch & Luce, 1999). What statistical properties drive the acquisition of such constraints? Because they are naturally highly correlated, previous…
Descriptors: Phonology, Probability, Learning Processes, Syllables
Zamora, Ángela; Súarez, José Manuel; Ardura, Diego – Journal of Educational Research, 2018
The authors' aim was to determine the extent to which error detection contributes to the explanation of a cognitive and motivational model of student performance in an assessment test. A total of 151 science students of secondary education participated in the investigation. Two causal models were developed using a structural equation analysis.…
Descriptors: Foreign Countries, Secondary School Students, Private Schools, Error Patterns
Leighton, Jacqueline P.; Tang, Wei; Guo, Qi – Assessment & Evaluation in Higher Education, 2018
The objective of the present study was to better understand a relatively under-researched topic, namely, undergraduate students' attitudes towards mistakes and how their attitudes relate to academic achievement. A series of online surveys were administered to a sample of 207 first- and second-year undergraduate students. Using structural…
Descriptors: Undergraduate Students, Student Attitudes, Error Patterns, Academic Achievement
Streeter, Matthew – International Educational Data Mining Society, 2015
We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing [7], which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…
Descriptors: Probability, Error Patterns, Learning Processes, Models
Liu, Ran; Koedinger, Kenneth R. – International Educational Data Mining Society, 2015
A growing body of research suggests that accounting for student specific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a…
Descriptors: Models, Regression (Statistics), Learning, Classification
Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
Van Inwegen, Eric G.; Adjei, Seth A.; Wang, Yan; Heffernan, Neil T. – International Educational Data Mining Society, 2015
User modelling algorithms such as Performance Factors Analysis and Knowledge Tracing seek to determine a student's knowledge state by analyzing (among other features) right and wrong answers. Anyone who has ever graded an assignment by hand knows that some answers are "more wrong" than others; i.e. they display less of an understanding…
Descriptors: Knowledge Level, Performance Factors, Error Patterns, Mathematics
Dirix, Nicolas; Cop, Uschi; Drieghe, Denis; Duyck, Wouter – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
The present study assessed intra- and cross-lingual neighborhood effects, using both a generalized lexical decision task and an analysis of a large-scale bilingual eye-tracking corpus (Cop, Dirix, Drieghe, & Duyck, 2016). Using new neighborhood density and frequency measures, the general lexical decision task yielded an inhibitory…
Descriptors: Decision Making, Second Language Learning, Word Frequency, Native Language
Middleton, Erica L.; Chen, Qi; Verkuilen, Jay – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
The study of homophones--words with different meanings that sound the same--has great potential to inform models of language production. Of particular relevance is a phenomenon termed "frequency" inheritance, where a low-frequency word (e.g., "deer") is produced more fluently than would be expected based on its frequency…
Descriptors: Aphasia, Word Frequency, Phonology, Naming
Merritt, Eileen G.; Palacios, Natalia; Banse, Holland; Rimm-Kaufman, Sara E.; Leis, Micela – Journal of Educational Research, 2017
Teachers need more clarity about effective teaching practices as they strive to help their low-achieving students understand mathematics. Our study describes the instructional practices used by two teachers who, by value-added metrics, would be considered "highly effective teachers" in classrooms with a majority of students who were…
Descriptors: Grade 5, Teaching Methods, Elementary School Mathematics, Mathematics Achievement
Foote, Rebecca – Second Language Research, 2015
In native speakers of gender-marking languages, mechanisms of gender production appear to be affected by the morphophonological cues to gender present in the noun phrase. This influence is manifested in higher levels of production accuracy when more transparent cues to gender are present in comparison to when they are not. The goal of the present…
Descriptors: Spanish, Grammar, Second Language Learning, Morphology (Languages)