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Observational studies can play a useful role in assessing the comparative effectiveness of competing treatments. In a clinical trial the randomization of participants to treatment and control groups generally results in well-balanced groups…

This paper considers endogenous selection models, in particular nonparametric ones. Estimating the unconditional law of the outcomes is possible when one uses instrumental variables. Using a selection equation which is additively separable…

Statistics Theory · Mathematics 2020-10-07 Eric Gautier

Copulas have now become ubiquitous statistical tools for describing, analysing and modelling dependence between random variables. Sklar's theorem, "the fundamental theorem of copulas", makes a clear distinction between the continuous case…

Methodology · Statistics 2019-02-12 Gery Geenens

The problem of testing instantaneous causality between variables with time-varying unconditional variance is investigated. It is shown that the classical tests based on the assumption of stationary processes must be avoided in our non…

Applications · Statistics 2014-04-14 Quentin Giai Gianetto , Hamdi Raissi

The instrumental variables (IV) method is a method for making causal inferences about the effect of a treatment based on an observational study in which there are unmeasured confounding variables. The method requires a valid IV, a variable…

Methodology · Statistics 2014-08-19 Dylan Small , Zhiqiang Tan , Scott Lorch , Alan Brookhart

In observational studies, instrumental variables estimation is greatly utilized to identify causal effects. One of the key conditions for the instrumental variables estimator to be consistent is the exclusion restriction, which indicates…

Methodology · Statistics 2020-06-16 Gyuhyeong Goh , Jisang Yu

An experiment is described which proves, using single photons only, that the standard hidden variables assumptions (commonly used to derive Bell inequalities) are inconsistent with quantum mechanics. The analysis is very simple and…

Quantum Physics · Physics 2007-06-22 Arnold Neumaier

It is common in instrumental variable studies for instrument values to be missing, for example when the instrument is a genetic test in Mendelian randomization studies. In this paper we discuss two apparent paradoxes that arise in so-called…

Methodology · Statistics 2018-04-19 Edward H. Kennedy , Dylan S. Small

This paper proposes semi-instrumental variables (semi-IVs) as an alternative to instrumental variables (IVs) to identify the causal effect of a binary (or discrete) endogenous treatment. A semi-IV is a less restrictive form of instrument:…

Econometrics · Economics 2025-09-23 Christophe Bruneel-Zupanc

Instrumental variables have been widely used for estimating the causal effect between exposure and outcome. Conventional estimation methods require complete knowledge about all the instruments' validity; a valid instrument must not have a…

Methodology · Statistics 2014-09-23 Hyunseung Kang , Anru Zhang , T. Tony Cai , Dylan S. Small

We study categorical instrumental variable (IV) models with instrument, treatment, and outcome taking finitely many values. We derive a simple closed-form characterization of the set of joint distributions of potential outcomes that are…

Statistics Theory · Mathematics 2025-11-13 Yilin Song , F. Richard Guo , K. C. Gary Chan , Thomas S. Richardson

Instrumental variable methods are widely used for inferring the causal effect in the presence of unmeasured confounders. Existing instrumental variable methods for nonlinear outcome models require stringent identifiability conditions. This…

Methodology · Statistics 2022-07-01 Sai Li , Zijian Guo

Sensitivity analysis informs causal inference by assessing the sensitivity of conclusions to departures from assumptions. The consistency assumption states that there are no hidden versions of treatment and that the outcome arising…

Methodology · Statistics 2025-12-29 Brian Knaeble , Qinyun Lin , Erich Kummerfeld , Kenneth A. Frank

The internal validity of observational study is often subject to debate. In this study, we define the unobserved sample based on the counterfactuals and formalize its relationship with the null hypothesis statistical testing (NHST) for…

Methodology · Statistics 2020-05-27 Tenglong Li , Kenneth A. Frank

The endogeneity issue is fundamentally important as many empirical applications may suffer from the omission of explanatory variables, measurement error, or simultaneous causality. Recently, \cite{hllt17} propose a "Deep Instrumental…

Statistics Theory · Mathematics 2020-05-01 Ruiqi Liu , Zuofeng Shang , Guang Cheng

Evaluating policy in imperfectly competitive markets requires understanding firm behavior. While researchers test conduct via model selection and assessment, we present advantages of Rivers and Vuong (2002) (RV) model selection under…

Econometrics · Economics 2024-01-18 Marco Duarte , Lorenzo Magnolfi , Mikkel Sølvsten , Christopher Sullivan

We describe a new Bell test for two-particle entangled systems that engages an unbounded continuous variable. The continuous variable state is allowed to be arbitrary and inaccessible to direct measurements. A systematic method is…

Quantum Physics · Physics 2014-01-20 X. -F. Qian , C. J. Broadbent , J. H. Eberly

Retrospective testing of predictive models does not consider the real-world context in which models are deployed. Prospective validation, on the other hand, enables meaningful comparisons between data generation processes by incorporating…

Machine Learning · Computer Science 2020-11-19 Steven Kearnes

In the above paper, it is claimed that with a particular use of the Bell inequality a simple single photon experiment could be performed to show the impossibility of any deterministic hidden variable theory in quantum optics. A careful…

Quantum Physics · Physics 2009-11-11 Aurelien Drezet

Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is unconfounded conditional on the observed…

Statistics Theory · Mathematics 2017-01-17 Peng Ding , Tyler VanderWeele , James Robins
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