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Fan Pan – ProQuest LLC, 2021
This dissertation informed researchers about the performance of different level-specific and target-specific model fit indices in Multilevel Latent Growth Model (MLGM) using unbalanced design and different trajectories. As the use of MLGMs is a relatively new field, this study helped further the field by informing researchers interested in using…
Descriptors: Goodness of Fit, Item Response Theory, Growth Models, Monte Carlo Methods
Zhu, Xiaoshu – ProQuest LLC, 2013
The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…
Descriptors: Item Response Theory, Models, Comparative Analysis, Goodness of Fit
Su, Yu-Lan – ProQuest LLC, 2013
This dissertation proposes two modified cognitive diagnostic models (CDMs), the deterministic, inputs, noisy, "and" gate with hierarchy (DINA-H) model and the deterministic, inputs, noisy, "or" gate with hierarchy (DINO-H) model. Both models incorporate the hierarchical structures of the cognitive skills in the model estimation…
Descriptors: Models, Diagnostic Tests, Cognitive Processes, Thinking Skills
Preston, Andrew James – ProQuest LLC, 2013
Response to intervention (RtI) is an approach to assist students with learning difficulties. There is limited research into the effectiveness of RtI within rural school districts. To address that gap, this quantitative, experimental study tested the theory of RtI, comparing the tier of intervention to oral reading fluency, controlling for…
Descriptors: Oral Reading, Reading Fluency, Reading Improvement, Hierarchical Linear Modeling