Estimation of Cognitive Ability in Longitudinal IRT using Univariate Composite Likelihood: Application to the Emory Healthy Brain Study Restricted; Files Only

Howard, Nicholas (Spring 2024)

Permanent URL: https://etd.library.emory.edu/concern/etds/5q47rq12x?locale=pt-BR
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Abstract

Longitudinal cognitive test data contain complex structures, particularly for the Item Response Theory model. Thus, available and accepted estimation methods in longitudinal Item Response Theory suffer from high computational intensity to extract the parameter estimates in the item. Univariate composite likelihood employs a marginal approach that broadens accessibility of estimating longitudinally-based parameters for reduced efficiency. Applying this method to the longitudinal item data from the Rey Auditory Verbal Learning Test, Multilingual Naming Test, and Judgment of Line Orientation test demonstrated that accounting for temporal correlation through robust variance estimators did not identify strong deviations away from the specified model. So, another element of the composite likelihood -- such as the latent trait, itself -- may be informative of the longitudinal aspect of the item data.

Table of Contents

1. Introduction 1

2. Background 3

2.1 Cognitive Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.2 Item Response Theory . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.3 Composite Likelihood . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3. Methods 8

3.1 Missing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4. Results 13

5. Discussion 22

Bibliography 25

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