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Dan Wei; Peida Zhan; Hongyun Liu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. The present study developed a versatile fit index, named Weighted Root Mean Squared Errors (WRMSE), based on individual case residuals (ICRs) with the aim…
Descriptors: Structural Equation Models, Goodness of Fit, Error of Measurement, Computation
Phillip K. Wood – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The logistic and confined exponential curves are frequently used in studies of growth and learning. These models, which are nonlinear in their parameters, can be estimated using structural equation modeling software. This paper proposes a single combined model, a weighted combination of both models. Mplus, Proc Calis, and lavaan code for the model…
Descriptors: Structural Equation Models, Computation, Computer Software, Weighted Scores
Castellano, Katherine E.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational Measurement, 2023
The simple average of student growth scores is often used in accountability systems, but it can be problematic for decision making. When computed using a small/moderate number of students, it can be sensitive to the sample, resulting in inaccurate representations of growth of the students, low year-to-year stability, and inequities for…
Descriptors: Academic Achievement, Accountability, Decision Making, Computation
Ramsay, James; Wiberg, Marie; Li, Juan – Journal of Educational and Behavioral Statistics, 2020
Ramsay and Wiberg used a new version of item response theory that represents test performance over nonnegative closed intervals such as [0, 100] or [0, n] and demonstrated that optimal scoring of binary test data yielded substantial improvements in point-wise root-mean-squared error and bias over number right or sum scoring. We extend these…
Descriptors: Scoring, Weighted Scores, Item Response Theory, Intervals
Wyse, Adam E. – Educational Measurement: Issues and Practice, 2020
One commonly used compromise standard-setting method is the Beuk (1984) method. A key assumption of the Beuk method is that the emphasis given to the pass rate and the percent correct ratings should be proportional to the extent that the panelists agree on their ratings. However, whether the slope of Beuk line reflects the emphasis that panelists…
Descriptors: Standard Setting (Scoring), Cutting Scores, Weighted Scores, Evaluation Methods
Shelby J. Haberman; Sabine Meinck; Ann-Kristin Koop – Large-scale Assessments in Education, 2024
This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal…
Descriptors: Elementary Secondary Education, Foreign Countries, Achievement Tests, Mathematics Achievement
Hansen, John; Sadler, Philip; Sonnert, Gerhard – Educational Measurement: Issues and Practice, 2019
The high school grade point average (GPA) is often adjusted to account for nominal indicators of course rigor, such as "honors" or "advanced placement." Adjusted GPAs--also known as weighted GPAs--are frequently used for computing students' rank in class and in the college admission process. Despite the high stakes attached to…
Descriptors: Grade Point Average, High School Students, Difficulty Level, Weighted Scores
Leite, Walter L.; Aydin, Burak; Gurel, Sungur – Journal of Experimental Education, 2019
This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove…
Descriptors: Probability, Weighted Scores, Monte Carlo Methods, Statistical Bias
Bishop, Crystal D.; Leite, Walter L.; Snyder, Patricia A. – Journal of Early Intervention, 2018
Data sets from large-scale longitudinal surveys involving young children and families have become available for secondary analysis by researchers in a variety of fields. Researchers in early intervention have conducted secondary analyses of such data sets to explore relationships between nonmalleable and malleable factors and child outcomes, and…
Descriptors: Probability, Weighted Scores, Statistical Bias, Data Analysis
Guzmán, Sebastián G. – Assessment & Evaluation in Higher Education, 2018
Group projects are widely used in higher education, but they can be problematic if all group members are given the same grade for a project to which they might not have contributed equally. Most scholars recommend addressing these problems by awarding individual grades, computing some kind of individual weighting factor (IWF) from peer and…
Descriptors: Monte Carlo Methods, Grades (Scholastic), Grading, Group Activities
Breyer, F. Jay; Rupp, André A.; Bridgeman, Brent – ETS Research Report Series, 2017
In this research report, we present an empirical argument for the use of a contributory scoring approach for the 2-essay writing assessment of the analytical writing section of the "GRE"® test in which human and machine scores are combined for score creation at the task and section levels. The approach was designed to replace a currently…
Descriptors: College Entrance Examinations, Scoring, Essay Tests, Writing Evaluation
Moses, Tim – Educational and Psychological Measurement, 2014
In this study, smoothing and scaling approaches are compared for estimating subscore-to-composite scaling results involving composites computed as rounded and weighted combinations of subscores. The considered smoothing and scaling approaches included those based on raw data, on smoothing the bivariate distribution of the subscores, on smoothing…
Descriptors: Weighted Scores, Scaling, Data Analysis, Comparative Analysis
Ganzfried, Sam; Yusuf, Farzana – Education Sciences, 2018
A problem faced by many instructors is that of designing exams that accurately assess the abilities of the students. Typically, these exams are prepared several days in advance, and generic question scores are used based on rough approximation of the question difficulty and length. For example, for a recent class taught by the author, there were…
Descriptors: Weighted Scores, Test Construction, Student Evaluation, Multiple Choice Tests
Kasim, Maznah Mat; Abdullah, Siti Rohana Goh – Malaysian Journal of Learning and Instruction, 2013
Purpose: It is a normal practice that students' overall scores are computed by simple average (SA) method which considers all academic subjects as having the same weights or same degree of importance. This paper highlights the application of simple weighted average (SWA) as an alternative method in aggregating students' academic achievements. The…
Descriptors: Weighted Scores, Academic Achievement, Student Evaluation, Case Studies
Qian, Jiahe; Jiang, Yanming; von Davier, Alina A. – ETS Research Report Series, 2013
Several factors could cause variability in item response theory (IRT) linking and equating procedures, such as the variability across examinee samples and/or test items, seasonality, regional differences, native language diversity, gender, and other demographic variables. Hence, the following question arises: Is it possible to select optimal…
Descriptors: Item Response Theory, Test Items, Sampling, True Scores
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