114 citations · 302 across the 21 of their papers we have counts for
12 papers · 1 filter
Individual Causation with Biased Data
Monica Musio, Philip Dawid
We consider the problem of assessing whether, in an individual case, there is a causal relationship between an observed exposure and a response variable. When data are available on…
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…
Bounding Causes of Effects with Mediators
Philip Dawid, Macartan Humphreys, Monica Musio
Suppose X and Y are binary exposure and outcome variables, and we have full knowledge of the distribution of Y, given application of X. From this we know the average causal effect…
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…
New bounds for the Probability of Causation in Mediation Analysis
Rossella Murtas, Alexander Philip Dawid, Monica Musio
An individual has been subjected to some exposure and has developed some outcome. Using data on similar individuals, we wish to evaluate, for this case, the probability that the ou…
A Note on Bayesian Model Selection for Discrete Data Using Proper Scoring Rules
A. Philip Dawid, Monica Musio, Silvia Columbu
We consider the problem of choosing between parametric models for a discrete observable, taking a Bayesian approach in which the within-model prior distributions are allowed to be…
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…
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…
Bayesian Model Selection Based on Proper Scoring Rules
A. Philip Dawid, Monica Musio
Bayesian model selection with improper priors is not well-defined because of the dependence of the marginal likelihood on the arbitrary scaling constants of the within-model prior…
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…
Theory and Applications of Proper Scoring Rules
A. Philip Dawid, Monica Musio
We give an overview of some uses of proper scoring rules in statistical inference, including frequentist estimation theory and Bayesian model selection with improper priors.
From Statistical Evidence to Evidence of Causality
Philip Dawid, Monica Musio, Stephen E. Fienberg
While statisticians and quantitative social scientists typically study the "effects of causes" (EoC), Lawyers and the Courts are more concerned with understanding the "causes of ef…