Using data from multiple studies to develop a child growth correlation matrix
Sign Up to like & getrecommendations! Published in 2018 at "Statistics in Medicine"
DOI: 10.1002/sim.7696
Abstract: In many countries, the monitoring of child growth does not occur in a regular manner, and instead, we may have to rely on sporadic observations that are subject to substantial measurement error. In these countries,… read more here.
Keywords: matrix; correlation matrix; child growth; growth ... See more keywords
Multivariate single index modeling of longitudinal data with multiple responses.
Sign Up to like & getrecommendations! Published in 2023 at "Statistics in medicine"
DOI: 10.1002/sim.9763
Abstract: In medical studies, composite indices and/or scores are routinely used for predicting medical conditions of patients. These indices are usually developed from observed data of certain disease risk factors, and it has been demonstrated in… read more here.
Keywords: longitudinal data; index; multiple responses; data multiple ... See more keywords
An improved procedure for sub-core property characterization using data from multiple coreflooding experiments
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Greenhouse Gas Control"
DOI: 10.1016/j.ijggc.2020.103226
Abstract: Abstract Sub-core properties of reservoir rocks are known to have a substantial impact on core-scale flow and saturation distribution, particularly considering CO2-brine coreflooding. Estimating these properties is important for various applications, e.g., investigation of capillary… read more here.
Keywords: procedure; sub core; coreflooding experiments; data multiple ... See more keywords
Comparing and integrating US COVID-19 data from multiple sources with anomaly detection and repairing
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2021.1928016
Abstract: Over the past few months, the outbreak of Coronavirus disease (COVID-19) has been expanding over the world. A reliable and accurate dataset of the cases is vital for scientists to conduct related research and for… read more here.
Keywords: covid; comparing integrating; integrating covid; data multiple ... See more keywords
Improving flux predictions by integrating data from multiple strains
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DOI: 10.1093/bioinformatics/btw706
Abstract: Motivation: Incorporating experimental data into constraint‐based models can improve the quality and accuracy of their metabolic flux predictions. Unfortunately, routinely and easily measured experimental data such as growth rates, extracellular fluxes, transcriptomics and even proteomics… read more here.
Keywords: improving flux; predictions integrating; flux predictions; multiple strains ... See more keywords
Assumptions and analysis planning in studies with missing data in multiple variables: moving beyond the MCAR/MAR/MNAR classification.
Sign Up to like & getrecommendations! Published in 2023 at "International journal of epidemiology"
DOI: 10.1093/ije/dyad008
Abstract: Researchers faced with incomplete data are encouraged to consider whether their data are 'missing completely at random' (MCAR), 'missing at random' (MAR) or 'missing not at random' (MNAR) when planning their analysis. However, there are… read more here.
Keywords: mcar; multiple variables; missing data; mar ... See more keywords
Erratum to: OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations
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DOI: 10.1186/s12864-017-3849-5
Abstract: 1. Saccaromyces should be spelt Saccharomyces in Table 1. (Table 1) 2. Kluveromyces should be spelt Kluyveromyces in Table 1. (Table 1) 3. Table 4, columns 3, 5, 7 and 9: All values within these… read more here.
Keywords: utilising data; erratum orthofiller; table table; orthofiller utilising ... See more keywords