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Philip Dawid
STATISTICAL SCIENCE Volume 36, Number 3 August 2021
A Matching Based Theoretical Framework for Estimating Probability of Causation
December 2000
ALEXANDER PHILIP DAWID Emeritus Professor of Statistics University of Cambridge E-Mail:
[email protected]
Web
Theory and Applications of Proper Scoring Rules
PHIL 8670 (Fall, 2015): Philosophy of Statistics
Computational and Financial Econometrics (CFE 2017)
Hyper and Structural Markov Laws for Graphical Models
Probability Forecasts and Prediction Markets A
Extended Conditional Independence and Applications in Causal Inference
Sufficient Covariate, Propensity Variable and Doubly Robust
Decision-Theoretic Foundations for Statistical Causality
Comparing Bayesian Models of Annotation
The Hammersley-Clifford Theorem and Its Impact on Modern Statistics
Fiducial Inference Then And
Epidemiology, Risk and Causation Conceptual and Methodological Issues in Public Health Science Alex Broadbent Background
Causal Inference from Experimental Data
Sufficient Covariates and Linear Propensity Analysis
Top View
Officers Number, Part I
Guide for Advocates on Statistics and Probability
Proper Local Scoring Rules 3
Causal Inference Without Counterfactuals
Status of the CCSA Session on International Statistics at the ISI World Statistics Congress in Hong Kong Prepared by the European Central Bank
Graphical Models for Forensic Analysis A. Philip Dawid, University Of
Beware of the DAG!
Challenges in Causality Volume 1
Using Stacking to Average Bayesian Predictive Distributions (With Discussion)
Conformal Predictive Distributions with Kernels
Historical Gregynog Statistical Conferences
ALEXANDER PHILIP DAWID Emeritus Professor of Statistics University of Cambridge E-Mail:
[email protected]
Web
Training Workpackage
Two Lectures: Bayesian Inference in a Nutshell and the Perils & Promise
Decision-Theoretic Foundations for Statistical Causality
Direct and Indirect Effects of Sequential Treatments
The Logic of Counterfactuals in Causal Inference
Causal Inference Isn't What You Think It Is
Beyond Subjective and Objective in Statistics
By Professor Philip Dawid Professor of Statistics Statistical Laboratory University of Cambridge
University Officers, Part I, 2016-17, Vol
The 59Th World Statistics Congress of the International Statistical Institute
2011Philstat.Pdf
Understanding the Use of Statistical Evidence in Courts and Tribunals
A Proposal for Informative Default Priors Scaled by the Standard Error of Estimates Arxiv:2011.15037V1 [Stat.ME] 30 Nov 2020
A. P. DAWID Publications