Zobrazeno 1 - 10
of 430
pro vyhledávání: '"Georg Heinze"'
Autor:
Georg Heinze, Mark Baillie, Lara Lusa, Willi Sauerbrei, Carsten Oliver Schmidt, Frank E. Harrell, Marianne Huebner, on behalf of TG2 and TG3 of the STRATOS initiative
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-17 (2024)
Abstract Statistical regression models are used for predicting outcomes based on the values of some predictor variables or for describing the association of an outcome with predictors. With a data set at hand, a regression model can be easily fit wit
Externí odkaz:
https://doaj.org/article/35d89449aa4d48d6b4d27c06c91e3ec0
Autor:
Theresa Ullmann, Georg Heinze, Lorena Hafermann, Christine Schilhart-Wallisch, Daniela Dunkler, for TG2 of the STRATOS initiative
Publikováno v:
PLoS ONE, Vol 19, Iss 8, p e0308543 (2024)
Researchers often perform data-driven variable selection when modeling the associations between an outcome and multiple independent variables in regression analysis. Variable selection may improve the interpretability, parsimony and/or predictive acc
Externí odkaz:
https://doaj.org/article/669b6b02a63e4172801891781b56dc04
Publikováno v:
Diagnostic and Prognostic Research, Vol 7, Iss 1, Pp 1-11 (2023)
Abstract Background The performance of models for binary outcomes can be described by measures such as the concordance statistic (c-statistic, area under the curve), the discrimination slope, or the Brier score. At internal validation, data resamplin
Externí odkaz:
https://doaj.org/article/760b5b135b4544219cf5edfd59bb8510
Autor:
Manja Deforth, Caroline E. Gebhard, Susan Bengs, Philipp K. Buehler, Reto A. Schuepbach, Annelies S. Zinkernagel, Silvio D. Brugger, Claudio T. Acevedo, Dimitri Patriki, Benedikt Wiggli, Raphael Twerenbold, Gabriela M. Kuster, Hans Pargger, Joerg C. Schefold, Thibaud Spinetti, Pedro D. Wendel-Garcia, Daniel A. Hofmaenner, Bianca Gysi, Martin Siegemund, Georg Heinze, Vera Regitz-Zagrosek, Catherine Gebhard, Ulrike Held
Publikováno v:
Diagnostic and Prognostic Research, Vol 6, Iss 1, Pp 1-11 (2022)
Abstract Background The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID sympto
Externí odkaz:
https://doaj.org/article/683c9ba713cb425b8c158e6f5bb2b80c
Autor:
Wolf Eilenberg, Mohammed A. Waduud, Henry Davies, Marc A. Bailey, D. Julian A. Scott, Florian Wolf, Anna Sotir, Sebastian Lakowitsch, Alexandra Kaider, Georg Heinze, Christine Brostjan, Christoph M. Domenig, Christoph Neumayer
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 10 (2023)
ObjectiveThis retrospective study evaluates the performance of UK National Institute for Health and Care Excellence (NICE) Guidelines on management of ruptured abdominal aortic aneurysms in a “real world setting” by emulating a hypothetical targe
Externí odkaz:
https://doaj.org/article/fc4e84c6c31e4ba8a9f9d650acbaa758
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-13 (2022)
Abstract Background Variable selection for regression models plays a key role in the analysis of biomedical data. However, inference after selection is not covered by classical statistical frequentist theory, which assumes a fixed set of covariates i
Externí odkaz:
https://doaj.org/article/362454f9d174433abefe626b3d98eb69
Autor:
Timea Mariann Helter, Alexander Kaltenboeck, Josef Baumgartner, Franz Mayrhofer, Georg Heinze, Andreas Sönnichsen, Johannes Wancata, Judit Simon
Publikováno v:
Health and Quality of Life Outcomes, Vol 20, Iss 1, Pp 1-12 (2022)
Abstract Background Some capability dimensions may be more important than others in determining someone’s well-being, and these preferences might be dependent on ill-health experience. This study aimed to explore the relative preference weights of
Externí odkaz:
https://doaj.org/article/376f8c3ce18845e5b9f839c2d01844a7
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-13 (2022)
Abstract Background In binary logistic regression data are ‘separable’ if there exists a linear combination of explanatory variables which perfectly predicts the observed outcome, leading to non-existence of some of the maximum likelihood coeffic
Externí odkaz:
https://doaj.org/article/e71399e608304345aecb8419f0ae81e8
Autor:
Mariella Gregorich, Federico Melograna, Martina Sunqvist, Stefan Michiels, Kristel Van Steen, Georg Heinze
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-17 (2022)
Abstract Background Recent advances in biotechnology enable the acquisition of high-dimensional data on individuals, posing challenges for prediction models which traditionally use covariates such as clinical patient characteristics. Alternative form
Externí odkaz:
https://doaj.org/article/2bb4b10128d94f64a6adf926e6423e89
Autor:
Christine Wallisch, Asan Agibetov, Daniela Dunkler, Maria Haller, Matthias Samwald, Georg Dorffner, Georg Heinze
Publikováno v:
BMC Medical Research Methodology, Vol 21, Iss 1, Pp 1-12 (2021)
Abstract Background While machine learning (ML) algorithms may predict cardiovascular outcomes more accurately than statistical models, their result is usually not representable by a transparent formula. Hence, it is often unclear how specific values
Externí odkaz:
https://doaj.org/article/fd44f25d547f4647968170b6e258fe2e