Optimizing Consistency and Coverage in Configurational Causal Modeling

Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the optimally obtainable consistency and coverage scores for data δ, so far, is a matter of repeatedly applying CCMs to δ while varying threshold settings. This article introduces a procedure called ConCovOpt that calculates, prior to actual CCM analyses, the consistency and coverage scores that can optimally be obtained by models inferred from δ. Moreover, we show how models reaching optimal scores can be methodically built in case of crisp-set and multi-value data. ConCovOpt is a tool, not for blindly maximizing model fit, but for rendering transparent the space of viable models at optimal fit scores in order to facilitate informed model selection—which, as we demonstrate by various data examples, may have substantive modeling implications.publishedVersio

The PC Algorithm and the Inference to Constitution

Gebharter has proposed using one of the best known Bayesian network causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this article is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in the widespread non-compliance of mechanistic systems with PC’s assumptions. This casts severe doubts on the attempt to implicitly define constitution as a form of deterministic direct causation complying with PC’s assumptions.acceptedVersio

Configurational Causal Modeling and Logic Regression

Configurational comparative methods (CCMs) and logic regression methods (LRMs) are two families of exploratory methods that employ very different techniques to analyze data generated by causal structures featuring conjunctural causation and equifinality. Aiming for the same by different means carries a substantive synergy potential, which, however, remains untapped so far because representatives of the two frameworks know little of each other. The purpose of this article is to change that. We first level the field for readers from both backgrounds by providing brief introductions to the basic ideas behind CCMs and LRMs. Then, we carve out the strengths and weaknesses of the two method families by benchmarking their performance when applied to binary data under a variety of different discovery contexts. It turns out that CCMs and LRMs have complementary strengths and weaknesses. This creates various promising avenues for cross-validation.publishedVersio

Von Wissen zur Performanz in der Ausbildung von sportunterrichtenden Lehrpersonen: Eine Delphi-Studie und ein Pretest zur inhaltlichen Validierung der Testinstrumente

The basis for evaluating the effectiveness of interventions in the education and continuing professional development of physical education (PE) teachers involves valid, reliable, and objective instruments, which are largely lacking. Content validity is a necessary basis for the development of such instruments. Accordingly, this study presents the content validation of a test for the assessment of (classroom management-related) professional knowledge and the perception, interpretation, and decision-making (PID) of prospective PE teachers. The result is a content-validated knowledge test (110 test items) as well as a video-based test for the assessment of PID (ten vignettes, 217 items). In a next step, the instruments are empirically validated. (DIPF/Orig.)Die Basis zur Eruierung der Effektivität von Interventionen in der Aus- und Weiterbildung von sportunterrichtenden Lehrpersonen stellen valide, reliable und objektive Instrumente dar, die weitgehend fehlen. Zur Entwicklung derartiger Instrumente ist die Inhaltsvalidität eine notwendige Grundlage. In vorliegender Studie wird dementsprechend die inhaltliche Validierung eines Tests zur Erfassung des (jeweils klassenführungsbezogenen) professionellen Wissens und der Wahrnehmung, Interpretation und Entscheidung (PID) bei (angehenden) sportunterrichtenden Lehrpersonen dargestellt. Es resultiert ein inhaltlich validierter Wissenstest (110 Testitems) sowie ein videobasierter Test zur Erfassung der PID (zehn Vignetten, 217 Items). In einem nächsten Schritt werden die Instrumente empirisch validiert. (DIPF/Orig.

Robustness and Model Selection in Configurational Causal Modeling

In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal structures, rendering it impossible to determine exactly how they influence the correctness of selected models. This article develops a computable criterion of fit-robustness, which quantifies the degree to which a CCM model agrees with other models inferred from the same data under systematically varied threshold settings of fit parameters. Based on two extended series of inverse search trials on data simulated from known causal structures, the article moreover provides a precise assessment of the degree to which fit-robustness scoring is conducive to finding a correct causal model and how it compares to other approaches of model selection.publishedVersio

Spectroradiometer Calibration for Radiance Transfer Measurements

Optical remote sensing and Earth observation instruments rely on precise radiometric calibrations which are generally provided by the broadband emission from large-aperture integrating spheres. The link between the integrating sphere radiance and an SI-traceable radiance standard is made by spectroradiometer measurements. In this work, the calibration efforts of a Spectra Vista Corporation (SVC) HR-1024i spectroradiometer are presented to study how these enable radiance transfer measurements at the Calibration Home Base (CHB) for imaging spectrometers at the Remote Sensing Technology Institute (IMF) of the German Aerospace Center (DLR). The spectral and radiometric response calibrations of an SVC HR-1024i spectroradiometer are reported, as well as the measurements of non-linearity and its sensitivity to temperature changes and polarized light. This achieves radiance transfer measurements with the calibrated spectroradiometer with relative expanded uncertainties between 1% and 3% (k=2) over the wavelength range of 380 nm to 2500 nm, which are limited by the uncertainties of the applied radiance standard

Spectroradiometer calibration for radiance transfer measurements

Optical remote sensing and Earth observation instruments rely on precise radiometric calibrations which are generally provided by the broadband emission from large-aperture integrating spheres. The link between the integrating sphere radiance and an SI-traceable radiance standard is made by spectroradiometer measurements. In this talk, the calibration efforts of a Spectra Vista Corporation (SVC) HR-1024i spectroradiometer are shown and how these enable radiance transfer measurements at the Calibration Home Base (CHB) for imaging spectrometers at the Remote Sensing Technology Institute (IMF) of the German Aerospace Center (DLR). Using this calibrated spectroradiometer, radiance transfer measurements are performed with relative expanded uncertainties between 1% and 3% (k = 2) over the wavelength range from 380 nm to 2500 nm, which are limited by the uncertainties of the applied radiance standard

Revealing the Purpose of a Stakeholder Organisation: The Case of a Public University Responding to the COVID-19 'Corona' Crisis

In early March 2020, Austria declared a state of emergency due to COVID-19. Social life was put on hold, public and private organisations were largely shut down, and universities had to adapt their operations. A group of WU academics investigate how one of Europe's biggest public universities in business and economics responded to the crisis and in the process rediscovered its core purpose

Extension and reconstruction theorems for the Urysohn universal metric space

We prove some extension theorems involving uniformly continuous maps of the universal Urysohn space. We also prove reconstruction theorems for certain groups of autohomeomorphisms of this space and of its open subsets.Comment: Final and shortened version, 25 pages, to appear in Czechoslovak Math.

Coincidence analysis: a new method for causal inference in implementation science

Background Implementation of multifaceted interventions typically involves many diverse elements working together in interrelated ways, including intervention components, implementation strategies, and features of local context. Given this real-world complexity, implementation researchers may be interested in a new mathematical, cross-case method called Coincidence Analysis (CNA) that has been designed explicitly to support causal inference, answer research questions about combinations of conditions that are minimally necessary or sufficient for an outcome, and identify the possible presence of multiple causal paths to an outcome. CNA can be applied as a standalone method or in conjunction with other approaches and can reveal new empirical findings related to implementation that might otherwise have gone undetected. Methods We applied CNA to a publicly available dataset from Sweden with county-level data on human papillomavirus (HPV) vaccination campaigns and vaccination uptake in 2012 and 2014 and then compared CNA results to the published regression findings. Results The original regression analysis found vaccination uptake was positively associated only with the availability of vaccines in schools. CNA produced different findings and uncovered an additional solution path: high vaccination rates were achieved by either (1) offering the vaccine in all schools or (2) a combination of offering the vaccine in some schools and media coverage. Conclusions CNA offers a new comparative approach for researchers seeking to understand how implementation conditions work together and link to outcomes.publishedVersio