Strengthening Causal Inference in Studies using Non-experimental Data: An Application of Propensity Score and Instrumental Variable Methods / 예방의학회지
Journal of Preventive Medicine and Public Health
;
: 495-504, 2007.
Article
Dans Coréen
| WPRIM
| ID: wpr-148076
ABSTRACT
OBJECTIVES:
This study attempts to show how studies using non-experimental data can strengthen causal inferences by applying propensity score and instrumental variable methods based on the counterfactual framework. For illustrative purposes, we examine the effect of having private health insurance on the probability of experiencing at least one hospital admission in the previous year.METHODS:
Using data from the 4th wave of the Korea Labor and Income Panel Study, we compared the results obtained using propensity score and instrumental variable methods with those from conventional logistic and linear regression models, respectively.RESULTS:
While conventional multiple regression analyses fail to identify the effect, the results estimated using propensity score and instrumental variable methods suggest that having private health insurance has positive and statistically significant effects on hospital admission.CONCLUSIONS:
This study demonstrates that propensity score and instrumental variable methods provide potentially useful alternatives to conventional regression approaches in making causal inferences using non-experimental data.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Admission du patient
/
Plan de recherche
/
Biais de sélection
/
Méthodes épidémiologiques
/
Analyse de régression
/
Interprétation statistique de données
/
Recherche sur les services de santé
/
Assurance maladie
/
Corée
Type d'étude:
Etude diagnostique
/
Étude pronostique
Limites du sujet:
Adulte
/
Femelle
/
Humains
/
Mâle
Pays comme sujet:
Asie
langue:
Coréen
Texte intégral:
Journal of Preventive Medicine and Public Health
Année:
2007
Type:
Article
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