Drawing causal inferences using propensity scores: a practical guide for community psychologists.
Am J Community Psychol
; 52(3-4): 380-92, 2013 Dec.
Article
em En
| MEDLINE
| ID: mdl-24185755
ABSTRACT
Confounding present in observational data impede community psychologists' ability to draw causal inferences. This paper describes propensity score methods as a conceptually straightforward approach to drawing causal inferences from observational data. A step-by-step demonstration of three propensity score methods-weighting, matching, and subclassification-is presented in the context of an empirical examination of the causal effect of preschool experiences (Head Start vs. parental care) on reading development in kindergarten. Although the unadjusted population estimate indicated that children with parental care had substantially higher reading scores than children who attended Head Start, all propensity score adjustments reduce the size of this overall causal effect by more than half. The causal effect was also defined and estimated among children who attended Head Start. Results provide no evidence for improved reading if those children had instead received parental care. We carefully define different causal effects and discuss their respective policy implications, summarize advantages and limitations of each propensity score method, and provide SAS and R syntax so that community psychologists may conduct causal inference in their own research.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Psicologia
/
Leitura
/
Desenvolvimento Infantil
/
Intervenção Educacional Precoce
/
Pontuação de Propensão
Tipo de estudo:
Etiology_studies
/
Incidence_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Child, preschool
/
Female
/
Humans
/
Male
Idioma:
En
Revista:
Am J Community Psychol
Ano de publicação:
2013
Tipo de documento:
Article