A Distinction between Causal Effects in Structural and Rubin Causal Models

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Analyzing Individual and Average Causal Effects via Structural Equation Models

Although both individual and average causal effects are defined in Rubin’s approach to causality, in this tradition almost all papers center around learning about the average causal effects. Almost no efforts deal with developing designs and models to learn about individual effects. This paper takes a first step in this direction. In the first and general part, Rubin’s concepts of individual an...

متن کامل

RUNNING HEAD: Causal models A philosophical investigation of causal interpretation in structural equation models

This paper is a brief overview and evaluation of current mathematical/statistical causal models, including the structural equation model (SEM), TETRAD, and the graphical model. The efficacy of these approaches will be discussed in the philosophical context of the Duhem-Quine thesis, realism, simplicity, identifiability (testability), empirical adequacy, and probabilistic causality. The emphasis...

متن کامل

Negotiation for Calculating Causal Effects in Bi-Agent Causal Models

In this paper we introduce the paradigm of multi-agent causal models (MACM), which are an extension of causal graphical models to a setting where there is no longer one single computational entity (agent) observing or not observing all the domain variables V. Instead there are several agents each having access to non-disjoint subsets of V. The incentive for introducing cooperative multiagent mo...

متن کامل

Identification of Causal Effects in Multi-Agent Causal Models

In this paper we introduce multi-agent causal models (MACMs) which are an extension of causal Bayesian networks to a multi-agent setting. Instead of 1 single agent modeling the entire domain, there are several agents each modeling non-disjoint subsets of the domain. Every agent has a causal model, determined by an acyclic causal diagram and a joint probability distribution over its observed var...

متن کامل

Causal Search in Structural Vector Autoregressive Models

This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first setting the underlying system is linear with normal disturbances and the structural model is identified by exploiting the information incorporated in the partial correlations of the estimated residuals. Zero partial co...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: SSRN Electronic Journal

سال: 2015

ISSN: 1556-5068

DOI: 10.2139/ssrn.2587076