Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Citado por Google
- Similares en SciELO
- Similares en Google
Compartir
Universitas Psychologica
versión impresa ISSN 1657-9267
Resumen
PINEDA, DAVID A et al. CLUSTER TAXOMETRY OF ATTENTION DEFICIT/ HYPERACTIVITY DISORDER WITH LATENT CLASS AND CORRESPONDENCE ANALYSIS. Univ. Psychol. [online]. 2007, vol.6, n.2, pp.409-423. ISSN 1657-9267.
Attention deficit/hyperactivity disorder (ADHD) has heterogeneous symptoms with diverse grades of severity. Latent class cluster analysis (LCCA) can be used to classify children, using direct data from any instrument that reports these symptoms, without previous gold standard diagnosis. One ADHD symptoms checklist, and one ADHD comorbidities questionnaire were used. LCCAs were developed for each instrument, which were administered to a sample of 540 children and adolescents, aged 4-17 years, from the regular school of Manizales-Colombia. A simple correspondence analysis (SCA) was done to determine the relationships between the groups classified from both LCCAs. Six clusters were obtained from ADHD checklist and five from the ADHD comorbidities questionnaire. SCA found four independent groups, derived from the concordances between the 11 clusters obtained by the LCCAs from both instruments. These findings suggest that LCCA and SCA can be use as accurate taxometric procedures to classify externalizing psychopathologies.
Palabras clave : ADHD; inattention; hyperactivity; latent class; correspondence analysis; taxometry.