Results 71 to 80 of about 4,525,334 (379)
Detecting Selection Bias in Meta-Analyses with Multiple Outcomes: A Simulation Study
Journal of Experimental Education, 2019 This study explores the performance of classical methods for detecting publication bias—namely, Egger’s regression test, Funnel Plot test, Begg’s Rank Correlation and Trim and Fill method—in meta-analysis of studies that report multiple effects ...
Belén Fernández-Castilla +5 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić +31 more
wiley +1 more source
Science Advances, 2018 Selection bias calls into question whether natural regeneration is really more successful than active tropical forest restoration. Several recent meta-analyses have aimed to determine whether natural regeneration is more effective at recovering tropical ...
J. L. Reid, M. Fagan, R. Zahawi
semanticscholar +1 more source
Causally Regularized Learning with Agnostic Data Selection Bias [PDF]
ACM Multimedia, 2017 Most of previous machine learning algorithms are proposed based on the i.i.d. hypothesis. However, this ideal assumption is often violated in real applications, where selection bias may arise between training and testing process.
Zheyan Shen +4 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.The authors applied joint/mixed models that predict mortality of trifluridine/tipiracil‐treated metastatic colorectal cancer patients based on circulating tumor DNA (ctDNA) trajectories. Patients at high risk of death could be spared aggressive therapy with the prospect of a higher quality of life in their remaining lifetime, whereas patients with a ...
Matthias Unseld +7 more
wiley +1 more source
Environmental Data Science, 2022 Residential energy efficiency programs play an important role in combating climate change. More precise quantification of the magnitude and timing of energy savings would bring large system benefits, allowing closer integration of energy efficiency into ...
Evan D. Sherwin +2 more
doaj +1 more source
Biometrics, 2019 Health research using electronic health records (EHR) has gained popularity, but misclassification of EHR‐derived disease status and lack of representativeness of the study sample can result in substantial bias in effect estimates and can impact power ...
Lauren J. Beesley, B. Mukherjee
semanticscholar +1 more source
Berkson's Bias, Selection Bias, and Missing Data [PDF]
Epidemiology, 2012 Although Berkson's bias is widely recognized in the epidemiologic literature, it remains underappreciated as a model of both selection bias and bias due to missing data. Simple causal diagrams and 2 × 2 tables illustrate how Berkson's bias connects to collider bias and selection bias more generally, and show the strong analogies between Berksonian ...
openaire +3 more sources
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Frontiers in Sports and Active Living, 2020 FC Barcelona is a multi-sport organization that adopts a talent identification approach that emphasizes the technical, psychological, and perceptual–cognitive attributes. It is unclear within this type of sporting selection model whether the relative age
Greg Doncaster +4 more
doaj +1 more source