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Published in 2024 at "Statistics in Medicine"
DOI: 10.1002/sim.10260
Abstract: In observational health services research, researchers often use clustered data to estimate the independent association between individual outcomes and several cluster‐level covariates after adjusting for individual‐level characteristics. Generalized estimating equations are a popular method for…
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Keywords:
cluster level;
number clusters;
variance;
level ... See more keywords
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Published in 2019 at "Wireless Personal Communications"
DOI: 10.1007/s11277-019-06131-5
Abstract: Most of the current Mobile Ad hoc Network (MANET) nodes are battery powered devices with different processing and data handling capacities. The ratio of sensitive data is increasing rapidly day-by-day. Providing Security with moderate power…
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Keywords:
security selection;
cluster level;
security;
energy ... See more keywords
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Published in 2025 at "Nature Communications"
DOI: 10.1038/s41467-025-61628-x
Abstract: RNA velocity inference is a valuable tool for understanding cell development, differentiation, and disease progression. However, existing RNA velocity inference methods typically rely on explicit assumptions of ordinary differential equations (ODE), which prohibits them from…
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Keywords:
cluster level;
velocity estimation;
rna velocity;
inference ... See more keywords
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Published in 2024 at "Nanoscale"
DOI: 10.1039/d4nr03047h
Abstract: Au25(SG)18 (SG: glutathione) nanoclusters, characterized by their atomically precise structures, exhibit near-infrared II (NIR-II) fluorescence emission and excellent biocompatibility, making them highly promising for imaging applications. However, their comparatively low photoluminescence quantum yield (QY) in…
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Keywords:
cluster level;
au25 nanoclusters;
nir fluorescence;
single cluster ... See more keywords
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Published in 2022 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2021.1994364
Abstract: Recently, there has been growing interest in using machine learning methods for causal inference due to their automatic and flexible ability to model the propensity score and the outcome model. However, almost all the machine…
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Keywords:
causal inference;
level unmeasured;
unmeasured confounding;
cluster level ... See more keywords
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Published in 2018 at "International journal of epidemiology"
DOI: 10.1093/ije/dyy057
Abstract: Background: Cluster randomised trials (CRTs) are increasingly used to assess the effectiveness of health interventions. Three main analysis approaches are: cluster-level analyses, mixed-models and generalized estimating equations (GEEs). Mixed models and GEEs can lead to…
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Keywords:
number clusters;
cluster level;
small number;
cluster ... See more keywords
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Published in 2022 at "Clinical Trials"
DOI: 10.1177/17407745221087465
Abstract: Trial designs using cluster-level randomization are necessary when interventions have intended effects that cannot be measured with individual randomization. When an intervention is intrinsically only able to be delivered to a cluster or when implementation…
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Keywords:
evaluation;
cluster randomized;
cluster;
randomized trials ... See more keywords
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Published in 2021 at "Frontiers in Public Health"
DOI: 10.3389/fpubh.2021.799536
Abstract: Background To date, there is a lack of sufficient evidence on the type of clusters in which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is most likely to spread. Notably, the differences between cluster-level and…
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Keywords:
sars cov;
level;
cluster level;
transmissibility ... See more keywords