Analysis of time-to-event for observational studies: Guidance to the use of intensity models

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.Comment: 28 pages, 12 figures. For associated Supplementary material, see http://publicifsv.sund.ku.dk/~pka/STRATOSTG8

P.A.M. Dirac and the Discovery of Quantum Mechanics

Dirac's contributions to the discovery of non-relativistic quantum mechanics and quantum electrodynamics, prior to his discovery of the relativistic wave equation, are described

Development and validation of the Treatment Related Impact Measure of Weight (TRIM-Weight)

<p>Abstract</p> <p>Background</p> <p>The use of prescription anti-obesity medication (AOM) is becoming increasingly common as treatment options grow and become more accessible. However, AOM may not be without a wide range of potentially negative impacts on patient functioning and well being. The Treatment Related Impact Measure (TRIM-Weight) is an obesity treatment-specific patient reported outcomes (PRO) measure designed to assess the key impacts of prescription anti-obesity medication. This paper will present the validation findings for the TRIM-Weight.</p> <p>Methods</p> <p>The online validation battery survey was administered in four countries (the U.S., U.K., Australia, and Canada). Eligible subjects were over age eighteen, currently taking a prescription AOM and were currently or had been obese during their life. Validation analyses were conducted according to an <it>a priori </it>statistical analysis plan. Item level psychometric and conceptual criteria were used to refine and reduce the preliminary item pool and factor analysis to identify structural domains was performed. Reliability and validity testing was then performed and the minimally importance difference (MID) explored.</p> <p>Results</p> <p>Two hundred and eight subjects completed the survey. Twenty-one of the 43 items were dropped and a five-factor structure was achieved: Daily Life, Weight Management, Treatment Burden, Experience of Side Effects, and Psychological Health. <it>A-priori </it>criteria for internal consistency and test-retest coefficients for the total score and all five subscales were met. All pre-specified hypotheses for convergent and known group validity were also met with the exception of the domain of Daily Life (proven in an ad hoc analysis) as well as the 1/2 standard deviation threshold for the MID.</p> <p>Conclusion</p> <p>The development and validation of the TRIM-Weight has been conducted according to well-defined principles for the creation of a PRO measure. Based on the evidence to date, the TRIM-Weight can be considered a brief, conceptually sound, valid and reliable PRO measure.</p

Opening science to society:how to progress societal engagement into (open) science policies

A broad understanding of the aims and objectives of the international open science movement was recently adopted with the 2021 UNESCO Recommendation on Open Science, expanding the focus of open science to include scientific knowledge, infrastructures, knowledge systems and the open engagement of societal actors. In response, recent discussions on science policy practice are shifting to the implementation of open science via national policy. While policy instruments to support some aspects of open science are well-studied, guidance on the emerging ‘social’ aspects of open science has lagged, prompting UNESCO to generate guidance. In this paper, authors of a UNESCO Open Science Toolkit guidance document on ‘Engaging societal actors in Open Science’ synthesize the scholarly underpinnings behind the guidance document's recommendations. This work draws upon a targeted search from academic, policy, and grey literature in the fields of open science and community engagement, with a special focus on citizen science, to derive guidance on how to overcome barriers to the uptake of societal engagement approaches. The results present building blocks of what an enabling environment for the open engagement of societal actors could look like, identifying key considerations and reflecting on opportunities and challenges for progressing and evaluating sound open engagement of societal actors into regional &amp; national (open) science policies

Opening science to society:how to progress societal engagement into (open) science policies

A broad understanding of the aims and objectives of the international open science movement was recently adopted with the 2021 UNESCO Recommendation on Open Science, expanding the focus of open science to include scientific knowledge, infrastructures, knowledge systems and the open engagement of societal actors. In response, recent discussions on science policy practice are shifting to the implementation of open science via national policy. While policy instruments to support some aspects of open science are well-studied, guidance on the emerging ‘social’ aspects of open science has lagged, prompting UNESCO to generate guidance. In this paper, authors of a UNESCO Open Science Toolkit guidance document on ‘Engaging societal actors in Open Science’ synthesize the scholarly underpinnings behind the guidance document's recommendations. This work draws upon a targeted search from academic, policy, and grey literature in the fields of open science and community engagement, with a special focus on citizen science, to derive guidance on how to overcome barriers to the uptake of societal engagement approaches. The results present building blocks of what an enabling environment for the open engagement of societal actors could look like, identifying key considerations and reflecting on opportunities and challenges for progressing and evaluating sound open engagement of societal actors into regional &amp; national (open) science policies

Application of Building Typologies for Modelling the Energy Balance of the Residential Building Stock

Building typologies can serve as a basis for analysing the national housing sector. During the TABULA project which was introducing or further developing building typologies in thirteen EU countries, six of the European partners have carried out model calculations which aim at imaging the energy consumption and estimating the energy saving potentials of their national residential building stocks (IWU / Germany, NOA / Greece, POLITO / Italy, VITO / Belgium, STU-K / Czech Republic, SBi / Denmark). The results show that the model calculations can provide plausible projections of the energy consumption of the national residential buildings stock. The fit of model calculations and national energy statistics is satisfactory, deviations can often be explained and corrected by adapting standard boundary conditions of the applied calculation models to more realistic values. In general, the analysis shows that building typologies can be a helpful tool for modelling the energy consumption of national building stocks and for carrying out scenario analysis beyond the TABULA project. The consideration of a set of representative buildings makes it possible to have a detailed view on various packages of measures for the complete buildings stock or for its sub-categories. The effects of different insulation measures at the respective construction elements as well as different heat supply measures including renewable energies can be considered in detail. The quality of future model calculations will depend very much on the availability of statistical data. For reliable scenario analysis information is necessary about the current state of the building stock (How many buildings and heating systems have been refurbished until now?) and about the current trends (How many buildings and heating systems are being refurbished every year?). The availability and regular update of the relevant statistical data will be an important basis for the development and evaluation of national climate protection strategies in the building secto