Articles with "imputation methods" as a keyword



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Sequential modeling for a class of reference‐based imputation methods in clinical trials with quantitative or binary outcomes

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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… read more here.

Keywords: reference; imputation methods; reference based; treatment ... See more keywords
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Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi

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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,… read more here.

Keywords: imputation; effects missing; prioritization; characterizing effects ... See more keywords

Assessment of the performance of different imputation methods for low-coverage sequencing in Holstein cattle.

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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… read more here.

Keywords: imputation methods; coverage sequencing; holstein cattle; low coverage ... See more keywords
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Empirical Comparison of Imputation Methods for Multivariate Missing Data in Public Health

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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… read more here.

Keywords: imputation methods; health; public health; missing data ... See more keywords