138 citations · 533 across the 19 of their papers we have counts for
20 papers
What Is a Causal Graph?
Philip Dawid
This article surveys the variety of ways in which a directed acyclic graph (DAG) can be used to represent a problem of probabilistic causality. For each of these we describe the re…
Personalised Decision-Making without Counterfactuals
A. Philip Dawid, Stephen Senn
This article is a response to recent proposals by Pearl and others for a new approach to personalised treatment decisions, in contrast to the traditional one based on statistical d…
Effects of Causes and Causes of Effects
A. Philip Dawid, Monica Musio
We describe and contrast two distinct problem areas for statistical causality: studying the likely effects of an intervention ("effects of causes"), and studying whether there is a…
Key Questions for Modelling COVID-19 Exit Strategies
Robin N Thompson, T Deirdre Hollingsworth, Valerie Isham +40
Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to impl…
The Probability of Causation
Philip Dawid, Monica Musio, Rossella Murtas
Many legal cases require decisions about causality, responsibility or blame, and these may be based on statistical data. However, causal inferences from such data are beset by subt…
Extended Conditional Independence and Applications in Causal Inference
Panayiota Constantinou, A. Philip Dawid
The goal of this paper is to integrate the notions of stochastic conditional independence and variation conditional independence under a more general notion of extended conditional…
Rejoinder to "Bayesian Model Selection Based on Proper Scoring Rules"
A. Philip Dawid, Monica Musio
We are deeply appreciative of the initiative of the editor, Marina Vanucci, in commissioning a discussion of our paper, and extremely grateful to all the discussants for their insi…
A Commentary on Statistical Assessment of Violence Recidivism Risk
Peter B. Imrey, A. Philip Dawid
Increasing integration and availability of data on large groups of persons has been accompanied by proliferation of statistical and other algorithmic prediction tools in banking, i…
Bounding the Probability of Causation in Mediation Analysis
A. P. Dawid, R. Murtas, M. Musio
Given empirical evidence for the dependence of an outcome variable on an exposure variable, we can typically only provide bounds for the "probability of causation" in the case of a…
Discussion of "On the Birnbaum Argument for the Strong Likelihood Principle"
A. P. Dawid
Deborah Mayo claims to have refuted Birnbaum's argument that the Likelihood Principle is a logical consequence of the Sufficiency and Conditionality Principles. However, this claim…
Statistical Causality from a Decision-Theoretic Perspective
A. Philip Dawid
We present an overview of the decision-theoretic framework of statistical causality, which is well-suited for formulating and solving problems of determining the effects of applied…
Minimum scoring rule inference
Philip Dawid, Monica Musio, Laura Ventura
Proper scoring rules are methods for encouraging honest assessment of probability distributions. Just like likelihood, a proper scoring rule can be applied to supply an unbiased es…
Stochastic Mechanistic Interaction
Carlo Berzuini, A. Philip Dawid
We propose a fully probabilistic formulation of the notion of mechanistic interaction (interaction in some fundamental mechanistic sense) between the effects of putative (possibly…
A Formal Treatment of Sequential Ignorability
A. Philip Dawid, Panayiota Constantinou
Taking a rigorous formal approach, we consider sequential decision problems involving observable variables, unobservable variables, and action variables. We can typically assume th…
Identifying Optimal Sequential Decisions
Philip Dawid, Vanessa Didelez
We consider conditions that allow us to find an optimal strategy for sequential decisions from a given data situation. For the case where all interventions are unconditional (atomi…
Retrospective-prospective symmetry in the likelihood and Bayesian analysis of case-control studies
Simon P. J. Byrne, A. Philip Dawid
Prentice & Pyke (1979) established that the maximum likelihood estimate of an odds-ratio in a case-control study is the same as would be found by running a logistic regression: in…
Proper local scoring rules
Matthew Parry, A. Philip Dawid, Steffen Lauritzen
We investigate proper scoring rules for continuous distributions on the real line. It is known that the log score is the only such rule that depends on the quoted density only thro…
Deep determinism and the assessment of mechanistic interaction between categorical and continuous variables
Carlo Berzuini, A. Philip Dawid
Our aim is to detect mechanistic interaction between the effects of two causal factors on a binary response, as an aid to identifying situations where the effects are mediated by a…
Identifying the consequences of dynamic treatment strategies: A decision-theoretic overview
A. Philip Dawid, Vanessa Didelez
We consider the problem of learning about and comparing the consequences of dynamic treatment strategies on the basis of observational data. We formulate this within a probabilisti…
Jeffreys's law for general games of prediction: in search of a theory
A. P. Dawid, V. G. Vovk
We are interested in the following version of Jeffreys's law: if two predictors are predicting the same sequence of events and either is doing a satisfactory job, they will make si…