The exploratory Generalized Noisy Inputs, Deterministic “OR” gate model: A duality proof and application

"Cognitive diagnosis models (CDMs) are useful methods for classifying individuals into substantively meaningful latent classes. Recent research applied disjunctive models to psychopathology questionnaires to support clinical diagnoses. We discuss a more general disjunctive model than used in previous research, the Generalized, Noisy Inputs, Deterministic ""OR'' Gate (GNIDO) model. We generalize the proof of Köhn & Chiu (2016) to establish the duality between the GNIDO and the Generalized, Noisy Inputs, Deterministic ""AND'' Gate (GNIDA) model, which is also known as the reduced reparameterized unified model (rRUM). We apply an exploratory GNIDO model to 14 anxiety items from the Wisconsin Longitudinal Study to uncover the latent structure. Our application of the exploratory GNIDO demonstrates the clinical value in using exploratory CDMs in applied research. We discuss the implication of our results for future methodological research as well as substantive efforts that aim to use clinical diagnoses to transition patients to symptom-free classes with more targeted interventions."

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2020

Author dc:creator

• Jimenez, Auburn A.

Contributors dc:contributor

• Culpepper, Steven
• Regenwetter, Michel

• Exploratory cognitive diagnosis modeling
• duality
• conjunctive
• disjunctive
• reduced reparameterized unified model
• psychopathology

Statement dc:rights

• Copyright 2019 Auburn Jimenez

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/106399

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/106399