Results 21 to 30 of about 375,599 (291)
Imputation for Repeated Bounded Outcome Data: Statistical and Machine-Learning Approaches
Mathematics, 2021 Real-life data are bounded and heavy-tailed variables. Zero-one-inflated beta (ZOIB) regression is used for modelling them. There are no appropriate methods to address the problem of missing data in repeated bounded outcomes.
Urko Aguirre-Larracoechea +1 more
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K Nearest Neighbor Imputation Performance on Missing Value Data Graduate User Satisfaction
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 A missing value is a common problem of most data processing in scientific research, which results in a lack of accuracy of research results. Several methods have been applied as a missing value solution, such as deleting all data that have a missing ...
Abdul Fadlil, Herman, Dikky Praseptian M
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A note on multiple imputation for method of moments estimation [PDF]
, 2015 Multiple imputation is a popular imputation method for general purpose estimation. Rubin(1987) provided an easily applicable formula for the variance estimation of multiple imputation.
Kim, Jae Kwang +2 more
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Outcome-sensitive multiple imputation: a simulation study
BMC Medical Research Methodology, 2017 Background Multiple imputation is frequently used to deal with missing data in healthcare research. Although it is known that the outcome should be included in the imputation model when imputing missing covariate values, it is not known whether it should
Evangelos Kontopantelis +3 more
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On the regression method of estimation of population mean from incomplete survey data through imputation [PDF]
, 2005 When some observations in the sample data are missing, the application of the regression method is considered for the estimation of population mean with and without the use of imputation.
Shalabh, Toutenburg, Helge
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Applied Sciences, 2022 The aim of this study is to ascertain the most suitable model for predicting complex odors using odor substance data that has a small number of data and a large number of missing data.
Do-Hyun Lee +3 more
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Bayesian Estimation of Disclosure Risks for Multiply Imputed, Synthetic Data
The Journal of Privacy and Confidentiality, 2014 Agencies seeking to disseminate public use microdata, i.e., data on individual records, can replace confidential values with multiple draws from statistical models estimated with the collected data.
Jerome P. Reiter +2 more
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Integration of Multimodal Data from Disparate Sources for Identifying Disease Subtypes
Biology, 2022 Studies over the past decade have generated a wealth of molecular data that can be leveraged to better understand cancer risk, progression, and outcomes.
Kaiyue Zhou +5 more
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Evaluating the Accuracy of Imputation Methods in a Five-Way Admixed Population
Frontiers in Genetics, 2019 Genotype imputation is a powerful tool for increasing statistical power in an association analysis. Meta-analysis of multiple study datasets also requires a substantial overlap of SNPs for a successful association analysis, which can be achieved by ...
Haiko Schurz +9 more
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Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research
Frontiers in Genetics, 2021 The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics.
Venceslas Douillard +8 more
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