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Marchini J: A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009
"... Genotype imputation methods are now being widely used in the analysis of genome-wide association studies. Most imputation analyses to date have used the HapMap as a reference dataset, but new reference panels (such as controls genotyped on multiple SNP chips and densely typed samples from the 1,000 ..."
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Cited by 449 (5 self)
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Genotype imputation methods are now being widely used in the analysis of genome-wide association studies. Most imputation analyses to date have used the HapMap as a reference dataset, but new reference panels (such as controls genotyped on multiple SNP chips and densely typed samples from the 1
ALTERNATIVE IMPUTATION METHODS FOR WAGE DATA
"... In this paper the results of an empirical investigation of different imputation methods for wage data and the ratio of wage to employment data are presented. This study is ..."
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Cited by 3 (2 self)
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In this paper the results of an empirical investigation of different imputation methods for wage data and the ratio of wage to employment data are presented. This study is
AN EVALUATION OF ALTERNATIVE IMPUTATION METHODS
"... Imputation is a method of adjusting for missing data. Missing responses to data items is a common problem in sample survey settings. These missing responses often occur because the respondent refuses or ..."
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Imputation is a method of adjusting for missing data. Missing responses to data items is a common problem in sample survey settings. These missing responses often occur because the respondent refuses or
DEVELOPMENT OF MODERN EDIT AND IMPUTATION METHODS AT
, 2002
"... Abstract: The development of modern edit and imputation (E&I) methods and software is one of the spearheads of the Methods and Informatics Department of Statistics Netherlands. Many aspects of E&I are covered by the work that is currently being carried out. Software development focuses on th ..."
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Abstract: The development of modern edit and imputation (E&I) methods and software is one of the spearheads of the Methods and Informatics Department of Statistics Netherlands. Many aspects of E&I are covered by the work that is currently being carried out. Software development focuses
Analyses and comparison of accuracy of different genotype imputation methods
- PLoS ONE
, 2008
"... The power of genetic association analyses is often compromised by missing genotypic data which contributes to lack of significant findings, e.g., in in silico replication studies. One solution is to impute untyped SNPs from typed flanking markers, based on known linkage disequilibrium (LD) relations ..."
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Cited by 13 (0 self)
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) relationships. Several imputation methods are available and their usefulness in association studies has been demonstrated, but factors affecting their relative performance in accuracy have not been systematically investigated. Therefore, we investigated and compared the performance of five popular genotype
A Survey: Classification of Imputation Methods in Data Mining
"... Abstract — In data mining one important stage is preprocessing. In which there are different mining tasks for it. In real world most of the data are noisy, inconsistent and incorrect. In fact, the most important step in pre-processing is filling (or handling) missing value. Missing data imputation i ..."
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Cited by 1 (0 self)
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is an important step in the process of machine learning and data mining when certain values are missed. In this paper, we have presented comparative review of the imputation method basically which are used for imputing missing values in the dataset. We have discussed the parametric, non-parametric and semi
A toolkit in SAS for the evaluation of multiple imputation methods
- Statistica Neerlandica
, 2003
"... This paper outlines a strategy to validate multiple imputation methods. Rubin’s criteria for proper multiple imputation are the point of departure. We describe a simulation method that yields insight into various aspects of bias and efficiency of the imputation process. We propose a new method for c ..."
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Cited by 4 (2 self)
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This paper outlines a strategy to validate multiple imputation methods. Rubin’s criteria for proper multiple imputation are the point of departure. We describe a simulation method that yields insight into various aspects of bias and efficiency of the imputation process. We propose a new method
A Study of K-Nearest Neighbour as an Imputation Method
- In HIS
, 2003
"... Data quality is a major concern in Machine Learning and other correlated areas such as Knowledge Discovery from Databases (KDD). As most Machine Learning algorithms induce knowledge strictly from data, the quality of the knowledge extracted is largely determined by the quality of the underlying data ..."
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Cited by 12 (0 self)
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into the knowledge induced. In this work, we analyse the use of the k-nearest neighbour as an imputation method. Imputation is a term that denotes a procedure that replaces the missing values in a data set by some plausible values. Our analysis indicates that missing data imputation based on the k-nearest neighbour
Influence of Outliers on Some Multiple Imputation Methods
"... In the field of data quality, imputation is the most used method for handling missing data. The performance of imputation techniques is influenced by various factors, especially when data represent only a sample of population, for example the survey design characteristics. In this paper, we compare ..."
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In the field of data quality, imputation is the most used method for handling missing data. The performance of imputation techniques is influenced by various factors, especially when data represent only a sample of population, for example the survey design characteristics. In this paper, we compare
Evaluation of Imputation Methods for Missing Data and Their Effect on the Reliability of Predictive Models
"... Abstract — In medical research, the problem of missing data occurs frequently. In this paper, eight imputation methods are evaluated based on accuracy and stability through a simulation experiment. The objective of this paper is to find appropriate methods for handling incomplete data sets during th ..."
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Abstract — In medical research, the problem of missing data occurs frequently. In this paper, eight imputation methods are evaluated based on accuracy and stability through a simulation experiment. The objective of this paper is to find appropriate methods for handling incomplete data sets during
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