In a causal graphical model, an instrument for a variable X and its effect Y is a ran­ dom variable that is a cause of X and in­ dependent of all the causes of Y except X (Pearl 1995). For continuous variables, in­ strumental variables can be used to estimate how the distribution of an effect will respond to a manipulation of its causes, even in the presence of unmeasured common causes (con­ fo...

BACKGROUND Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression. METHODS We included 29 088 patients (age >20 years) from 16 European national or regional renal registries who rec...

This paper presents a theoretical proposal of fuzzy instrumental variable (FIV) methods for nonlinear discrete time systems identification and parameter estimation in noisy environment based on the fuzzy instrumental variable concept. The theoretical analysis is presented using a suitable formulation associated to Takagi-Sugeno (TS) fuzzy model. The complexity of the algorithm is quite low and ...

In this paper, we propose an adaptive IIR equalizer based on prefiltering techniques. The proposed equalizer has a cascade structure of an ARMA prefilter and an adaptive FIR equalizer. The ARMA prefilter is designed based on the transfer function estimated by the gradient-type instrumental variable algorithm. Simulation results are shown to confirm the performance of the proposed adaptive IIR e...

This paper describes optimal instrumental variable methods for identifying discretetime transfer function models when the system operates in closed-loop. Several noise models required for the design of optimal prefilters and instruments are analyzed and different approaches are developed according to whether the controller is known or not. Moreover, a new optimal refined instrumental variable t...

In this paper, we present an extended set of graphical criteria for the identification of direct causal effects in linear Structural Equation Models (SEMs). Previous methods of graphical identification of direct causal effects in linear SEMs include methods such as the single-door criterion, the instrumental variable and the IV-pair, and the accessory set. However, there remain graphical models...

Instrumental Variable Estimation of Treatment Effects for Duration Outcomes In this article we propose and implement an instrumental variable estimation procedure to obtain treatment effects on duration outcomes. The method can handle the typical complications that arise with duration data of time-varying treatment and censoring. The treatment effect we define is in terms of shifting the quanti...

Learning a causal effect from observational data requires strong assumptions. One possibility is to use instrumental variables, which are typically justified by background knowledge. It is possible, under further assumptions, to discover whether a variable is structurally instrumental to a target causal effect X → Y . However, the few existing approaches are lacking on how general these assumpt...

BACKGROUND The assessment of the causal effect of Intensive Care Unit (ICU) admission generally involves usual observational designs and thus requires controlling for confounding variables. Instrumental variable analysis is an econometric technique that allows causal inferences of the effectiveness of some treatments during situations to be made when a randomized trial has not been or cannot be...