Using a nonparametric item response theory model to identify patterns of cognitive decline: The Mokken scale analysis
Using a nonparametric item response theory model to identify patterns of cognitive decline: The Mokken scale analysis
Authors
Calderon, Carlos
Palominos, Diego
Veliz Garcia, Oscar
Ramos Henderson, Miguel
Bekios Canales, Nikolas
Beyle, Christian
avalos Tejeda, Marcelo
Domic Siede, Marcos
Palominos, Diego
Veliz Garcia, Oscar
Ramos Henderson, Miguel
Bekios Canales, Nikolas
Beyle, Christian
avalos Tejeda, Marcelo
Domic Siede, Marcos
Profesor GuĆa
Authors
Date
Datos de publicaciĆ³n:
10.1111/jnp.12381
JOURNAL OF NEUROPSYCHOLOGY,Vol.,2024
Tipo de recurso
WOS
Keywords
Materia geogrƔfica
Collections
Abstract
Cognitive decline, particularly in dementia, presents complex challenges in early detection and diagnosis. While Item Response Theory (IRT) has been instrumental in identifying patterns of cognitive impairment through psychometric tests, its parametric models often require large sample sizes and strict assumptions. This creates a need for more adaptable, less demanding analytical methods. This study aimed to evaluate the effectiveness of Mokken scale analysis (MSA), a nonparametric IRT model, in identifying hierarchical patterns of cognitive impairment from psychometric tests. Using data from 1164 adults over 60 years old, we applied MSA to the orientation subscale of ACE-III. Our analysis involved calculating scalability, monotone homogeneity, invariant item ordering (IIO) and response functions. The MSA effectively retrieved the hierarchical order of cognitive impairment patterns. Most items showed strong scalability and consistent patterns of cognitive performance. However, challenges with IIO were observed, particularly with items having adjacent difficulty parameters. The findings highlight MSA's potential as a practical alternative to parametric IRT models in cognitive impairment research. Its ability to provide valuable insights into patterns of cognitive deterioration, coupled with less stringent requirements, makes it a useful tool for clinicians and researchers.