Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the meth...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
Precision medicine presents various methodological challenges whose assessment requires the consider...
used to alleviate confounding problems in nonexperimental studies on treatment effects, but it is no...
Instrumental variable (IV) methods are widely used in the health economics literature to adjust for ...
This study is motivated by the potential problem of using observational data to draw inferences abou...
Objectives: To contrast the interpretations of treatment effect esti-mates using risk adjustment and...
Instrumental variable (IV) analysis is used to address unmeasured confounding when comparing two non...
Instrumental variables (IV) is a central strategy for identifying causal effects in absence of rando...
Purpose: Propensity trimming, hierarchical modelling and instrumental variable (IV) analysis are sta...
Instrumental variable analysis (IVA) is used to control unobserved confounders and estimate average ...
Objectives Randomization can be used as an instrumental variable (IV) to account for unmeasured conf...
<p>Several methods have been proposed for partially or point identifying the average treatment effec...
This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
International audiencePurpose: Observational studies using routinely collected data are faced with a...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
Precision medicine presents various methodological challenges whose assessment requires the consider...
used to alleviate confounding problems in nonexperimental studies on treatment effects, but it is no...
Instrumental variable (IV) methods are widely used in the health economics literature to adjust for ...
This study is motivated by the potential problem of using observational data to draw inferences abou...
Objectives: To contrast the interpretations of treatment effect esti-mates using risk adjustment and...
Instrumental variable (IV) analysis is used to address unmeasured confounding when comparing two non...
Instrumental variables (IV) is a central strategy for identifying causal effects in absence of rando...
Purpose: Propensity trimming, hierarchical modelling and instrumental variable (IV) analysis are sta...
Instrumental variable analysis (IVA) is used to control unobserved confounders and estimate average ...
Objectives Randomization can be used as an instrumental variable (IV) to account for unmeasured conf...
<p>Several methods have been proposed for partially or point identifying the average treatment effec...
This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
International audiencePurpose: Observational studies using routinely collected data are faced with a...
This thesis unites three papers discussing different approaches for estimating treatment effects, ei...
Precision medicine presents various methodological challenges whose assessment requires the consider...
used to alleviate confounding problems in nonexperimental studies on treatment effects, but it is no...