arXiv subjects

Martin Huber

Publications and source records attributed to Martin Huber.

58 records · Page 4Linked to original sources

arXiv2019

Direct and Indirect Effects based on Changes-in-Changes

We propose a novel approach for causal mediation analysis based on changes-in-changes assumptions restricting unobserved heterogeneity over time. This allows disentangling the causal effect of a binary treatment on a continuous outcome into an indirect effect operating through a binary intermediate variable (called mediator) and a direct effect running via other causal mechanisms. We identify average and quantile direct and indirect effects for various subgroups under the condition that the outcome is monotonic in the unobserved heterogeneity and that the distribution of the latter does not change over time conditional on the treatment and the mediator. We also provide a simulation study and an empirical application to the Jobs II programme.

econ.EM↗

arXiv2019

An introduction to flexible methods for policy evaluation

This chapter covers different approaches to policy evaluation for assessing the causal effect of a treatment or intervention on an outcome of interest. As an introduction to causal inference, the discussion starts with the experimental evaluation of a randomized treatment. It then reviews evaluation methods based on selection on observables (assuming a quasi-random treatment given observed covariates), instrumental variables (inducing a quasi-random shift in the treatment), difference-in-differences and changes-in-changes (exploiting changes in outcomes over time), as well as regression discontinuities and kinks (using changes in the treatment assignment at some threshold of a running variable). The chapter discusses methods particularly suited for data with many observations for a flexible (i.e. semi- or nonparametric) modeling of treatment effects, and/or many (i.e. high dimensional) observed covariates by applying machine learning to select and control for covariates in a data-driven way. This is not only useful for tackling confounding by controlling for instance for factors jointly affecting the treatment and the outcome, but also for learning effect heterogeneities across subgroups defined upon observable covariates and optimally targeting those groups for which the treatment is most effective.

econ.EM↗

arXiv2019

Energy Loss Due to Defect Formation from $^{206}$Pb Recoils in SuperCDMS Germanium Detectors

The Super Cryogenic Dark Matter Search experiment (SuperCDMS) at the Soudan Underground Laboratory studied energy loss associated with Frenkel defect formation in germanium crystals at mK temperatures using in situ $^{210}$Pb sources. We examine the spectrum of $^{206}$Pb nuclear recoils near its expected 103 keV endpoint energy and determine an energy loss of $\left(6.08\pm0.18\right)$ %, which we attribute to defect formation. From this result and using TRIM simulations, we extract the first experimentally determined average displacement threshold energy of $\left(19.7^{+0.6}_{-0.5}\right)$ eV for germanium. This has implications for the analysis thresholds of future germanium-based dark matter searches.

physics.ins-det↗

arXiv2017

Design and Implementation of a Semantic Dialogue System for Radiologists

This chapter describes a semantic dialogue system for radiologists in a comprehensive case study within the large-scale MEDICO project. MEDICO addresses the need for advanced semantic technologies in the search for medical image and patient data. The objectives are, first, to enable a seamless integration of medical images and different user applications by providing direct access to image semantics, and second, to design and implement a multimodal dialogue shell for the radiologist. Speech-based semantic image retrieval and annotation of medical images should provide the basis for help in clinical decision support and computer aided diagnosis. We will describe the clinical workflow and interaction requirements and focus on the design and implementation of a multimodal user interface for patient/image search or annotation and its implementation while using a speech-based dialogue shell. Ontology modeling provides the backbone for knowledge representation in the dialogue shell and the specific medical application domain; ontology structures are the communication basis of our combined semantic search and retrieval architecture which includes the MEDICO server, the triple store, the semantic search API, the medical visualization toolkit MITK, and the speech-based dialogue shell, amongst others. We will focus on usability aspects of multimodal applications, our storyboard and the implemented speech and touchscreen interaction design.

cs.HC↗