Results 21 to 30 of about 26,362,948 (329)
Permutation-based group sequential analyses for cognitive neuroscience
NeuroImage, 2023 Cognitive neuroscientists have been grappling with two related experimental design problems. First, the complexity of neuroimaging data (e.g. often hundreds of thousands of correlated measurements) and analysis pipelines demands bespoke, non-parametric ...
John P. Veillette +2 more
doaj +1 more source
Continuous Post-Market Sequential Safety Surveillance with Minimum Events to Signal
Revstat Statistical Journal, 2017 Continuous sequential analysis is increasingly used for near real-time post-market drug and vaccine safety surveillance. We explore continuous sequential monitoring when the null cannot be rejected until a minimum number of adverse events have occurred.
Martin Kulldorff , Ivair R. Silva
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Nonexponential kinetics captured in sequential unfolding of polyproteins over a range of loads
Current Research in Structural Biology, 2022 While performing under mechanical loads in vivo, polyproteins are vitally involved in cellular mechanisms such as regulation of tissue elasticity and mechano-transduction by unfolding their comprising domains and extending them. It is widely thought that
Einat Chetrit +6 more
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An Alternative for Indicators that Characterize the Structure of Economic Systems
Entropy, 2017 Studies on the structure of economic systems are, most frequently, carried out by the methods of informational statistics. These methods, often accompanied by a broad range of indicators (Shannon entropy, Balassa coefficient, Herfindahl specialty index ...
Irina-Maria Dragan +1 more
doaj +1 more source
Infectious Diseases, 2021 Background In view of many unanswered clinical questions regarding treatment of COVID-19 with remdesivir, we systematically identified, critically appraised and summarized the findings from randomized controlled trials (RCTs) of remdesivir for COVID-19 ...
G. Okoli +5 more
semanticscholar +1 more source
SMCTC : sequential Monte Carlo in C++ [PDF]
, 2009 Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature.
Johansen, Adam M., Adam M. Johansen
core +1 more source
Cardiovascular Engineering and Technology, 2015 Several clinical studies have identified a strong correlation between neointimal hyperplasia following coronary stent deployment and both stent-induced arterial injury and altered vessel hemodynamics. As such, the sequential structural and fluid dynamics
David M Martin, Fergal Boyle
semanticscholar +1 more source
IEEE Access, 2018 This paper addresses the problem of monitoring online a non-stationary process to detect abrupt changes in the process mean value. Two main challenges are addressed: First, the monitored process is nonstationary; i.e., naturally changes over time and it ...
Karim Tout +2 more
doaj +1 more source
Anales de Psicologia, 2015 The study of change in repeated measures studies or longitudinal studies (cross-sectional and/or cross-sequential) is of considerable interest in the field of developmental psychology.
Elena Escolano-Pérez +1 more
doaj +1 more source
Frontiers in Cardiovascular Medicine, 2022 ObjectivesTo undertake a systematic review and meta-analysis of cohort studies to compare the patency and adverse outcomes of sequential and individual saphenous vein grafts (SVGs) in coronary artery bypass grafting (CABG).MethodsWe searched PubMed ...
He Jiao +6 more
doaj +1 more source