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Victoria Savalei; Yves Rosseel – Structural Equation Modeling: A Multidisciplinary Journal, 2022
This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Robustness (Statistics)
Klint Kanopka – ProQuest LLC, 2023
As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underlying interest in the cognitive processes and…
Descriptors: Scores, Computation, Data Interpretation, Behavior Patterns
Costa-Mendes, Ricardo; Oliveira, Tiago; Castelli, Mauro; Cruz-Jesus, Frederico – Education and Information Technologies, 2021
This article uses an anonymous 2014-15 school year dataset from the Directorate-General for Statistics of Education and Science (DGEEC) of the Portuguese Ministry of Education as a means to carry out a predictive power comparison between the classic multilinear regression model and a chosen set of machine learning algorithms. A multilinear…
Descriptors: Foreign Countries, High School Students, Grades (Scholastic), Electronic Learning
Slater, Stefan; Baker, Ryan – Distance Education, 2019
Considerable attention has been given to methods for knowledge estimation, a category of methods for automatic assessment of a student's degree of skill mastery or knowledge at a specific time. Knowledge estimation is frequently used to make decisions about when a student has reached mastery and is ready to advance to new material, but there has…
Descriptors: Prediction, Mastery Learning, Academic Achievement, Bayesian Statistics
Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
Widenhorn, Ralf – Physics Teacher, 2016
The Portland Timbers won their first Major League Soccer (MLS) Cup Championship in December 2015. However, if it had not been for a kind double goalpost miss during a penalty shootout a few weeks earlier, the Timbers would never have been in the finals. On Oct. 30th, after what has been called "the greatest penalty kick shootout in MLS…
Descriptors: Team Sports, Computation, Probability, Incidence
Porter, Kristin E.; Balu, Rekha; Gunton, Brad; Pestronk, Jefferson; Cohen, Allison – Society for Research on Educational Effectiveness, 2016
With the advent of data systems that allow for frequent or even real-time student data updates, and recognition that high school students often can move from being on-track to graduation to off-track in a matter of weeks, indicator analysis alone may not provide a complete picture to guide school leaders' actions. The authors of this paper suggest…
Descriptors: Graduation, High School Students, Public Schools, At Risk Students
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
National Centre for Vocational Education Research (NCVER), 2016
This work asks one simple question: "how reliable is the method used by the National Centre for Vocational Education Research (NCVER) to estimate projected rates of VET program completion?" In other words, how well do early projections align with actual completion rates some years later? Completion rates are simple to calculate with a…
Descriptors: Vocational Education, Graduation Rate, Predictive Measurement, Predictive Validity
Beaman, Belinda – Australian Primary Mathematics Classroom, 2013
As teachers we are encouraged to contextualize the mathematics that we teach. In this article, Belinda Beaman explains how she used the weather as a context for developing decimal understanding. We particularly enjoyed reading how the students were involved in estimating.
Descriptors: Teaching Methods, Arithmetic, Climate, Mathematics
Guarino, Cassandra M.; Reckase, Mark D.; Stacy, Brian W.; Wooldridge, Jeffrey M. – Education Policy Center at Michigan State University, 2014
We study the properties of two specification tests that have been applied to a variety of estimators in the context of value-added measures (VAMs) of teacher and school quality: the Hausman test for choosing between random and fixed effects and a test for feedback (sometimes called a "falsification test"). We discuss theoretical…
Descriptors: Achievement Gains, Evaluation Methods, Teacher Effectiveness, Educational Quality
Jongerling, Joran; Hamaker, Ellen L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article shows that the mean and covariance structure of the predetermined autoregressive latent trajectory (ALT) model are very flexible. As a result, the shape of the modeled growth curve can be quite different from what one might expect at first glance. This is illustrated with several numerical examples that show that, for example, a…
Descriptors: Statistics, Structural Equation Models, Scores, Predictor Variables
Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
Lin, Guixian – ProQuest LLC, 2009
The Cox proportional hazards model and the accelerated failure time model are frequently used in survival data analysis. They are powerful, yet have limitation due to their model assumptions. Quantile regression offers a semiparametric approach to model data with possible heterogeneity. It is particularly powerful for censored responses, where the…
Descriptors: Data Analysis, Computation, Probability, Simulation
Kolovelonis, Athanasios; Goudas, Marios; Dermitzaki, Irini – International Electronic Journal of Elementary Education, 2012
The aim of this study was to examine students' performance calibration in physical education. One hundred fifth and sixth grade students provided estimations regarding their performance in a dribbling test after practicing dribbling for 16 minutes under different self-regulatory conditions (i.e., receiving feedback, setting goals, self-recording).…
Descriptors: Elementary School Students, Physical Education, Team Sports, Grade 5
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