Results 31 to 40 of about 152 (62)

Potential outcomes and decision-theoretic foundations for statistical causality: Response to Richardson and Robins

Journal of Causal Inference
I thank Thomas Richardson and James Robins for their discussion of my article, and discuss the similarities and differences between their approach to causal modelling, based on single world intervention graphs, and my own decision-theoretic approach.
Dawid Philip
doaj   +1 more source

Estadística, societat i veritat [PDF]

, 2002
Se hace una exposición general de la incidencia de la estadística en la sociedad, desde una perspectiva histórica y actual. Los métodos y resultados de la estadística representan una forma actual e imprescindible del pensamiento, que abarca todos los ...
Cuadras, C. M.
core   +1 more source

From urn models to box models: Making Neyman's (1923) insights accessible

Journal of Causal Inference
Neyman’s 1923 paper introduced the potential outcomes framework and the foundations of randomization-based inference. We discuss the influence of Neyman’s paper on four introductory to intermediate-level textbooks by Berkeley faculty members (Scheffé ...
Lin Winston, Dudoit Sandrine, Nolan Deborah, Speed Terence P.   +3 more
doaj   +1 more source

Probability theory and its models

, 2008
This paper argues for the status of formal probability theory as a mathematical, rather than a scientific, theory. David Freedman and Philip Stark's concept of model based probabilities is examined and is used as a bridge between the formal theory and ...
Humphreys, Paul
core   +1 more source

Spillover detection for donor selection in synthetic control models

Journal of Causal Inference
Synthetic control (SC) models are widely used to estimate causal effects in settings with observational time-series data. To identify the causal effect on a target unit, SC requires the existence of additional units that are not impacted by the ...
O’Riordan Michael, Gilligan-Lee Ciarán M.   +1 more
doaj   +1 more source

On asymptotically optimal tests under loss of identifiability in semiparametric models [PDF]

, 2009
We consider tests of hypotheses when the parameters are not identifiable under the null in semiparametric models, where regularity conditions for profile likelihood theory fail.
Fine, Jason P., Kosorok, Michael R., Song, Rui   +2 more
core   +3 more sources

Decision making, symmetry and structure: Justifying causal interventions

Journal of Causal Inference
We can use structural causal models (SCMs) to help us evaluate the consequences of actions given data. SCMs identify actions with structural interventions. A careful decision maker may wonder whether this identification is justified.
Johnston David O., Ong Cheng Soon, Williamson Robert C.   +2 more
doaj   +1 more source

Where do statistical models come from? Revisiting the problem of specification

, 2006
R. A. Fisher founded modern statistical inference in 1922 and identified its fundamental problems to be: specification, estimation and distribution. Since then the problem of statistical model specification has received scant attention in the statistics ...
Spanos, Aris
core   +2 more sources

The shape of incomplete preferences

, 2006
Incomplete preferences provide the epistemic foundation for models of imprecise subjective probabilities and utilities that are used in robust Bayesian analysis and in theories of bounded rationality.
Nau, Robert
core   +3 more sources

Asymptotic inference for high-dimensional data

, 2010
In this paper, we study inference for high-dimensional data characterized by small sample sizes relative to the dimension of the data. In particular, we provide an infinite-dimensional framework to study statistical models that involve situations in ...
Kuelbs, Jim, Vidyashankar, Anand N.
core   +1 more source