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Persistent link: https://www.econbiz.de/10003563529
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This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so...
Persistent link: https://www.econbiz.de/10011309722
This paper provides inference methods for best linear approximations to functions which are known to lie within a band. It extends the partial identification literature by allowing the upper and lower functions defining the band to be any functions, including ones carrying an index, which can be...
Persistent link: https://www.econbiz.de/10009692055
We consider a high-dimensional regression model with a possible change-point due to a covariate threshold and develop the Lasso estimator of regression coefficients as well as the threshold parameter. Our Lasso estimator not only selects covariates but also selects a model between linear and...
Persistent link: https://www.econbiz.de/10010358938
This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so...
Persistent link: https://www.econbiz.de/10011459651
We consider estimation of a linear or nonparametric additive model in which a few coefficients or additive components are "large" and may be objects of substantive interest, whereas others are "small" but not necessarily zero. The number of small coefficients or additive components may exceed...
Persistent link: https://www.econbiz.de/10009567830
In a randomized control trial, the precision of an average treatment effect estimator can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. We propose the use of pre-experimental data such as a census, or a...
Persistent link: https://www.econbiz.de/10011446549
We propose a method to correct for sample selection in quantile regression models. Selection is modelled via the cumulative distribution function, or copula, of the percentile error in the outcome equation and the error in the participation decision. Copula parameters are estimated by minimizing...
Persistent link: https://www.econbiz.de/10011405705
Persistent link: https://www.econbiz.de/10001748185