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Jenss-Bayley Latent Change Score Model with Individual Ratio of the Growth Acceleration in the Framework of Individual Measurement Occasions
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Liu, Jin – Journal of Educational and Behavioral Statistics, 2022
Longitudinal data analysis has been widely employed to examine between-individual differences in within-individual changes. One challenge of such analyses is that the rate-of-change is only available indirectly when change patterns are nonlinear with respect to time. Latent change score models (LCSMs), which can be employed to investigate the…
Descriptors: Longitudinal Studies, Individual Differences, Scores, Models
How Grit-S Items Work in Measuring Growth: Focusing on Item Discrimination and Sensitivity to Change
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Lim, Hyo Jin; Lee, Sora – Journal of Psychoeducational Assessment, 2023
This study investigates how sensitively the current grit measure (Grit-S) is able to reflect the differences between individuals (i.e. item discrimination) and change within individuals (i.e. sensitivity to change of items) using longitudinal data. Data from the Korean Children and Youth Panel Study 2018 of elementary (fourth grade) and middle…
Descriptors: Individual Differences, Change, Elementary School Students, Middle School Students
Factors Affecting the Adequacy and Preferability of Semiparametric Groups-Based Approximations of Continuous Growth Trajectories
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Sterba, Sonya K.; Baldasaro, Ruth E.; Bauer, Daniel J. – Multivariate Behavioral Research, 2012
Psychologists have long been interested in characterizing individual differences in change over time. It is often plausible to assume that the distribution of these individual differences is continuous in nature, yet theory is seldom so specific as to designate its parametric form (e.g., normal). Semiparametric groups-based trajectory models…
Descriptors: Individual Differences, Change, Statistical Analysis, Models
Development of Occupational Aspiration Prestige: A Piecewise Latent Growth Model of Selected Influences
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Lee, In Heok; Rojewski, Jay W. – Journal of Vocational Behavior, 2009
Using the National Education Longitudinal Study of 1988 (NELS:88) data sets, the complex phenomenon of intra-individual and inter-individual differences in and the potential predictors of those differences on career aspirations development over a 12-year period was analyzed. Results indicated that 73.1% of the total growth (change) in adolescents'…
Descriptors: Individual Differences, Adolescents, Young Adults, Occupational Aspiration
Examining Interindividual Differences in Cyclicity of Pleasant and Unpleasant Affects Using Spectral Analysis and Item Response Modeling
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Ram, Nilam; Chow, Sy-Miin; Bowles, Ryan P.; Wang, Lijuan; Grimm, Kevin; Fujita, Frank; Nesselroade, John R. – Psychometrika, 2005
Weekly cycles in emotion were examined by combining item response modeling and spectral analysis approaches in an analysis of 179 college students' reports of daily emotions experienced over 7 weeks. We addressed the measurement of emotion using an item response model. Spectral analysis and multilevel sinusoidal models were used to identify…
Descriptors: Individual Differences, Item Response Theory, Models, College Students
An Optimal Unbiased Classification Rule for Mastery Testing Based on Longitudinal Data.
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Tan, E. S.; And Others – Educational and Psychological Measurement, 1995
An optimal unbiased classification rule is proposed based on a longitudinal model for the measurement of change in ability. In general, the rule predicts future level of knowledge by using information about level of knowledge at entrance, its rate of growth, and the amount of within-individual variation. (SLD)
Descriptors: Ability, Change, Classification, Individual Differences
A Measurement Model for Linking Individual Learning to Processes and Knowledge: Application to Mathematical Reasoning.
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Embretson, Susan E. – Journal of Educational Measurement, 1995
An extension of the multidimensional Rasch model for learning and change is presented that permits theories of processes and knowledge structures to be incorporated into the item response model. The extension resolves basic problems in measuring change and permits adaptive testing. The method is illustrated in a study of mathematical problem…
Descriptors: Adaptive Testing, Change, Individual Differences, Item Response Theory