Results 61 to 70 of about 1,718,863 (277)
Two-stage multiple imputation with a longitudinal composite variable
BMC Medical Research MethodologyBackground Missing data are common in longitudinal studies. Multiple imputation (MI) is widely used to handle missing data. However, most of the MI methods assume various missing data types as missing at random (MAR) in imputation.
Xuzhi Wang, Martin G. Larson, Chunyu Liu
doaj +1 more source
Enhancing imputation accuracy for catch-all missing data mechanisms with DFBETAS and leverage
Research in StatisticsThis paper addresses the challenge of missing data in scientific research. It specifically examines the case of missing data arising from a “catch-all” missing not at ran (MNAR) mechanism, where missing values are disproportionately from one category ...
Fares Qeadan, William A. Barbeau
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Generating Synthetic Missing Data: A Review by Missing Mechanism
IEEE Access, 2019 The performance evaluation of imputation algorithms often involves the generation of missing values. Missing values can be inserted in only one feature (univariate configuration) or in several features (multivariate configuration) at different ...
Miriam Seoane Santos +5 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook +6 more
wiley +1 more source
A survey on missing data in machine learning
Journal of Big Data, 2021 Machine learning has been the corner stone in analysing and extracting information from data and often a problem of missing values is encountered. Missing values occur because of various factors like missing completely at random, missing at random or ...
Tlamelo Emmanuel +5 more
doaj +1 more source
An Investigation of Missing Data Methods for Classification Trees [PDF]
, 2008 There are many different missing data methods used by classification tree algorithms, but few studies have been done comparing their appropriateness and performance.
Ding, Yufeng, Simonoff, Jeffrey S.
core
Coordinate-Descent Diffusion Learning by Networked Agents
, 2017 This work examines the mean-square error performance of diffusion stochastic algorithms under a generalized coordinate-descent scheme. In this setting, the adaptation step by each agent is limited to a random subset of the coordinates of its stochastic ...
Sayed, Ali H. +3 more
core +1 more source
Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM
FEBS Letters, EarlyView.Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley +1 more source
BMC Public HealthBackground Tobacco use is a major contributor to chronic illnesses worldwide, leading to significant morbidity and mortality. Effective tobacco cessation programs are crucial in reducing the health risks associated with smoking.
Mengting Zhao, Benjamin Langworthy
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Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source