Statistical and substantive inferences in public health: issues in the application of multilevel models.
Annu Rev Public Health
; 25: 53-77, 2004.
Article
em En
| MEDLINE
| ID: mdl-15015912
ABSTRACT
Multilevel statistical models have become increasingly popular among public health researchers over the past decade. Yet the enthusiasm with which these models are being adopted may obscure rather than solve some problems of statistical and substantive inference. We discuss the three most common applications of multilevel models in public health (a) cluster-randomized trials, (b) observational studies of the multilevel etiology of health and disease, and (c) assessments of health care provider performance. In each area of investigation, we describe how multilevel models are being applied, comment on the validity of the statistical and substantive inferences being drawn, and suggest ways in which the strengths of multilevel models might be more fully exploited. We conclude with a call for more careful thinking about multilevel causal inference.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Saúde Pública
/
Métodos Epidemiológicos
Tipo de estudo:
Clinical_trials
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Annu Rev Public Health
Ano de publicação:
2004
Tipo de documento:
Article
País de afiliação:
Estados Unidos