Abstract We develop a mathematical and interpretative foundation for the enterprise of decision-theoretic (DT) statistical causality, which is a straightforward way of representing and addressing causal questions. DT reframes causal inference as “assisted decision-making” and aims to...

Abstract I thank Ilya Shpitser for his comments on my article, and discuss the use of models with restricted interventions.

Abstract I thank Judea Pearl for his discussion of my paper and respond to the points he raises. In particular, his attachment to unaugmented directed acyclic graphs has led to a misapprehension of my own proposals. I also discuss the possibilities for developing a non-manipulative understanding...

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 causes. The approach is described in detail, and it is related to and contrasted with other current formulations,...

This letter comments on the report “Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-comparison Methods” released in September 2016, by the President's Council of Advisors on Science and Technology (PCAST). The report advocates a two-stage procedure for evaluation...

A scoring rule <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$S(x; q)$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mi>S</mi> <mo stretchy="false">(</mo> <mi>x</mi> <mo>;</mo> <mi>q</mi> <mo stretchy="false">)</mo> </mrow> </math> </EquationSource> </InlineEquation> provides a way of judging the quality of a quoted probability density <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$q$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>q</mi> </math> </EquationSource> </InlineEquation> for a random variable <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$X$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>X</mi> </math> </EquationSource> </InlineEquation> in the light of its outcome <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$$x$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>x</mi> </math> </EquationSource> </InlineEquation>. It is called proper if honesty is your best policy, i.e., when you believe <InlineEquation ID="IEq5"> <EquationSource Format="TEX">$$X$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>X</mi>...</math></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation></equationsource></equationsource></inlineequation>

The data that are analysed are from a monitoring survey which was carried out in 1994 in the forests of Baden-Württemberg, a federal state in the south-western region of Germany. The survey is part of a large monitoring scheme that has been carried out since the 1980s at different spatial and...