Results 11 to 20 of about 178,240 (253)
Missing Data and Imputation Methods. [PDF]
Anesth Analg, 2020 Schober P, Vetter TR.
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Imputation methods for mixed datasets in bioarchaeology. [PDF]
Archaeol Anthropol SciAbstractMissing data is a prevalent problem in bioarchaeological research and imputation could provide a promising solution. This work simulated missingness on a control dataset (481 samples × 41 variables) in order to explore imputation methods for mixed data (qualitative and quantitative data). The tested methods included Random Forest (RF), PCA/MCA,
Ryan-Despraz J, Wissler A.
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Methods to Handle Incomplete Data
MAMC Journal of Medical Sciences, 2020 Context: The major question for data analysis is determining the appropriate analytic approach in the presence of incomplete observations. The most common solution to handle missing data in a data set is imputation, where missing values are estimated and
Vinny Johny +2 more
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TIME SERIES IMPUTATION USING VAR-IM (CASE STUDY: WEATHER DATA IN METEOROLOGICAL STATION OF CITEKO)
Barekeng, 2022 Univariate imputation methods are defined as imputation methods that only use the information of the target variable to estimate missing values.
Muhammad Edy Rizal +2 more
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Assessment of genotype imputation methods [PDF]
BMC Proceedings, 2009 Abstract Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE.
Biernacka, Joanna M +9 more
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Comparison of multiple imputation and other methods for the analysis of imputed genotypes
BMC Genomics, 2023 Abstract Background Analysis of imputed genotypes is an important and routine component of genome-wide association studies and the increasing size of imputation reference panels has facilitated the ability to impute and test low-frequency variants for associations. In the context of genotype imputation, the true genotype
Paul L. Auer +4 more
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Imputation Methods for scRNA Sequencing Data
Applied Sciences, 2022 More and more researchers use single-cell RNA sequencing (scRNA-seq) technology to characterize the transcriptional map at the single-cell level. They use it to study the heterogeneity of complex tissues, transcriptome dynamics, and the diversity of ...
Mengyuan Wang +6 more
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Evaluating Proteomics Imputation Methods with Improved Criteria. [PDF]
J Proteome Res, 2023 Abstract Quantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. This missingness hinders reproducibility, reduces statistical power, and makes it difficult to compare across samples or experiments.
Harris L, Fondrie WE, Oh S, Noble WS.
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The ability of different imputation methods for missing values in mental measurement questionnaires
BMC Medical Research Methodology, 2020 Background Incomplete data are of particular important influence in mental measurement questionnaires. Most experts, however, mostly focus on clinical trials and cohort studies and generally pay less attention to this deficiency. We aim is to compare the
Xueying Xu +5 more
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A method for increasing the robustness of multiple imputation [PDF]
Computational Statistics & Data Analysis, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rhian M. Daniel, Michael G. Kenward
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