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Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9303
Abstract: We consider treatment effect estimation in a randomized clinical trial with longitudinally measured quantitative or categorical outcomes. To handle missing data, we usually assume missing at random and then conduct sensitivity analysis for missing not…
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Keywords:
reference;
imputation methods;
reference based;
treatment ... See more keywords
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Published in 2018 at "BioData Mining"
DOI: 10.1186/s13040-018-0169-5
Abstract: BackgroundThe Toxicological Priority Index (ToxPi) is a method for prioritization and profiling of chemicals that integrates data from diverse sources. However, individual data sources (“assays”), such as in vitro bioassays or in vivo study endpoints,…
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Keywords:
imputation;
effects missing;
prioritization;
characterizing effects ... See more keywords
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Published in 2022 at "Journal of dairy science"
DOI: 10.3168/jds.2021-21360
Abstract: Low-coverage sequencing (LCS) followed by imputation has been proposed as a cost-effective genotyping approach for obtaining genotypes of whole-genome variants. Imputation performance is essential for the effectiveness of this approach. Several imputation methods have been…
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Keywords:
imputation methods;
coverage sequencing;
holstein cattle;
low coverage ... See more keywords
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Published in 2023 at "International Journal of Environmental Research and Public Health"
DOI: 10.3390/ijerph20021524
Abstract: Sample estimates derived from data with missing values may be unreliable and may negatively impact the inferences that researchers make about the underlying population due to nonresponse bias. As a result, imputation is often preferred…
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Keywords:
imputation methods;
health;
public health;
missing data ... See more keywords