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Titolo:
MULTILEVEL ANALYSIS OF REPEATED-MEASURES DATA
Autore:
VANDERLEEDEN R;
Indirizzi:
LEIDEN UNIV,FAC SOCIAL SCI,DEPT PSYCHOL,UNIT PSYCHOMETR & RES METHODOL,POB 9555 NL-2300 RB LEIDEN NETHERLANDS
Titolo Testata:
Quality & quantity
fascicolo: 1, volume: 32, anno: 1998,
pagine: 15 - 29
SICI:
0033-5177(1998)32:1<15:MAORD>2.0.ZU;2-0
Fonte:
ISI
Lingua:
ENG
Soggetto:
HIERARCHICAL LINEAR-MODELS; LONGITUDINAL DATA;
Keywords:
REPEATED MEASURES; GROWTH CURVE ANALYSIS; LONGITUDINAL DATA; MULTILEVEL ANALYSIS; HIERARCHICAL LINEAR MODEL; HIERARCHICAL DATA;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
43
Recensione:
Indirizzi per estratti:
Citazione:
R. Vanderleeden, "MULTILEVEL ANALYSIS OF REPEATED-MEASURES DATA", Quality & quantity, 32(1), 1998, pp. 15-29

Abstract

Hierarchically structured data are common in many areas of scientificresearch. Such data are characterized by nested membership relations among the units of observation. Multilevel analysis is a class of methods that explicitly takes the hierarchical structure into account. Repeated measures data can be considered as having a hierarchical structure as well: measurements are nested within, for instance, individuals. In this paper, an overview is given of the multilevel analysis approach to repeated measures data. A simple application to growth curves isprovided as an illustration. It is argued that multilevel analysis ofrepeated measures data is a powerful and attractive approach for several reasons, such as flexibility, and the emphasis on individual development.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 10/07/20 alle ore 09:47:21