Results 31 to 40 of about 318,466 (281)
A Semiparametric Method of Multiple Imputation
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998 Summary In this paper, we describe how to use multiple imputation semiparametrically to obtain estimates of parameters and their standard errors when some individuals have missing data. The methods given require the investigator to know or be able to estimate the process generating the missing data but requires no full distributional ...
Lipsitz, Stuart R. +2 more
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Investigating Some Imputation Methods of Multivariate Imputation Chained Equations
European Journal of Mathematics and Statistics, 2022 This paper investigates three MICE methods: Predictive Mean Matching (PMM), Quantile Regression-based Multiple Imputation (QR-basedMI) and Simple Random Sampling Imputation (SRSI) at imputation numbers 5, 15, 20 and 30 with 5% and 20% missing values, to ascertain the one that produces imputed values that best matches the observed values and compare the
M. T. Nwakuya, E. O. Biu
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Advanced methods for missing values imputation based on similarity learning [PDF]
PeerJ Computer Science, 2021 The real-world data analysis and processing using data mining techniques often are facing observations that contain missing values. The main challenge of mining datasets is the existence of missing values.
Khaled M. Fouad +3 more
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Applied Medical Informatics, 2021 Background: Not all datasets are created equal. There are some happy scenarios when the researcher has the luxury of curating the dataset and ensuring all the desired fields are filled.
Marius FERSIGAN, Marius MĂRUȘTERI
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A new hybrid method for data analysis when a significant percentage of data is missing [PDF]
Journal of HyperstructuresThis article aims to compare the efficiency of different imputation methods with missing data. In this way we use mean, median, Expected-Maximization (EM), regression imputation(RI) and multiple imputations (MI) to replace missing data.In fact, we employ
Behrouz Fathi-Vajargah, Ahmad Nouraldin
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Imputation of ungenotyped individuals based on genotyped relatives using Machine Learning Methodology [PDF]
Journal of Epigenetics, 2021 Machine learning methods have been used in genetic studies to build models capable of predicting missing genotypes for both human and animal genetic variations. Genotype imputation is an important process of predicting unknown genotypes. The objective of
Naeem Rastin Bojnord +3 more
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Assessment of the performance of hidden Markov models for imputation in animal breeding
Genetics Selection Evolution, 2018 Background In this paper, we review the performance of various hidden Markov model-based imputation methods in animal breeding populations. Traditionally, pedigree and heuristic-based imputation methods have been used for imputation in large animal ...
Andrew Whalen +3 more
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An efficient ensemble method for missing value imputation in microarray gene expression data
BMC Bioinformatics, 2021 Background The genomics data analysis has been widely used to study disease genes and drug targets. However, the existence of missing values in genomics datasets poses a significant problem, which severely hinders the use of genomics data.
Xinshan Zhu +5 more
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SnapFISH-IMPUTE: an imputation method for multiplexed DNA FISH data
Communications BiologyABSTRACT Chromatin spatial organization plays a crucial role in gene regulation. Recently developed and prospering multiplexed DNA FISH technologies enable direct visualization of chromatin conformation in nucleus. However, incomplete data caused by limited detection efficiency can substantially complicate and impair ...
Hongyu Yu +4 more
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Multiple Imputation in a Longitudinal Cohort Study: A Case Study of Sensitivity to Imputation Methods [PDF]
American Journal of Epidemiology, 2014 Multiple imputation has entered mainstream practice for the analysis of incomplete data. We have used it extensively in a large Australian longitudinal cohort study, the Victorian Adolescent Health Cohort Study (1992-2008). Although we have endeavored to follow best practices, there is little published advice on this, and we have not previously ...
Romaniuk, Helena +2 more
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