INFORMATION

Psicothema was founded in Asturias (northern Spain) in 1989, and is published jointly by the Psychology Faculty of the University of Oviedo and the Psychological Association of the Principality of Asturias (Colegio Oficial de Psicología del Principado de Asturias).
We currently publish four issues per year, which accounts for some 100 articles annually. We admit work from both the basic and applied research fields, and from all areas of Psychology, all manuscripts being anonymously reviewed prior to publication.

PSICOTHEMA
  • Director: Laura E. Gómez Sánchez
  • Frequency:
         February | May | August | November
  • ISSN: 0214-9915
  • Digital Edition:: 1886-144X
CONTACT US
  • Address: Ildelfonso Sánchez del Río, 4, 1º B
    33001 Oviedo (Spain)
  • Phone: 985 285 778
  • Fax: 985 281 374
  • Email:psicothema@cop.es

Psicothema, 2007. Vol. Vol. 19 (nº 2). 308-321




Cómo ajustar e interpretar modelos multinivel con SPSS

Antonio Pardo, Miguel Ángel Ruiz y Rafael San Martín

Universidad Autónoma de Madrid

Los modelos jerárquicos o multinivel permiten analizar datos cuando los casos están agrupados en unidades de información más amplias y se toman medidas tanto en el nivel más bajo (los casos) como en los niveles más altos (los grupos). En este trabajo se describen los modelos multinivel comúnmente tratados en la literatura estadística y se explica cómo ajustarlos utilizando el SPSS (cualquier versión a partir de la 11) y cómo interpretar los resultados. En concreto se describen, ajustan e interpretan los siguientes modelos: (1) análisis de varianza de un factor de efectos aleatorios, (2) análisis de regresión con medias como resultados, (3) análisis de covarianza de un factor de efectos aleatorios, (4) análisis de regresión con coeficientes aleatorios y (5) análisis de regresión con medias y pendientes como resultados. Todos los modelos se describen intentando hacerlos comprensibles para los investigadores en ciencias del comportamiento y la salud.

How to fit and interpret multilevel models using SPSS. Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11th) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

PDF

Impact Factor JCR SSCI Clarivate 2023 = 3.2 (Q1) / CiteScore SCOPUS 2023 = 6.5 (Q1)