Mediating Instrumental Variables
نویسنده
چکیده
منابع مشابه
Instrumental Variables Regression with Measurement Errors and Multicollinearity in Instruments
In this paper we obtain a consistent estimator when there exist some measurement errors and multicollinearity in the instrumental variables in a two stage least square estimation of parameters. We investigate the asymptotic distribution of the proposed estimator and discuss its properties using some theoretical proofs and a simulation study. A real numerical application is also provided for mor...
متن کاملBias and Bias Correction in Multi-Site Instrumental Variables Analysis Of Heterogeneous Mediator Effects
We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the exclusion restriction. We use a random-coefficient...
متن کاملIdentification of Causal Parameters in Randomized Studies with Mediating Variables
Randomized trials are used to assess the effectiveness of one or more treatments in inducing outcomes of interest. Treatments are typically designed to target key mediating variables that are thought to be causally related to the outcome. Thus, researchers want to know not only if the treatment is effective, but how the mediators affect the outcome. Data from such studies are often analyzed usi...
متن کاملOn Searching for Generalized Instrumental Variables
Instrumental Variables are a popular way to identify the direct causal effect of a random variable X on a variable Y . Often no single instrumental variable exists, although it is still possible to find a set of generalized instrumental variables (GIVs) and identify the causal effect of all these variables at once. Till now it was not known how to find GIVs systematically or even test efficient...
متن کاملOn a Class of Bias-Amplifying Variables that Endanger Effect Estimates
This note deals with a class of variables that, if conditioned on, tends to amplify confounding bias in the analysis of causal effects. This class, independently discovered by Bhattacharya and Vogt (2007) and Wooldridge (2009), includes instrumental variables and variables that have greater influence on treatment selection than on the outcome. We offer a simple derivation and an intuitive expla...
متن کامل