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PRM68 Increased Accuracy of Distribution Based Missing Value Imputation: An Alternative to Mean Inputation in Real World Environment Survey Research

机译：PRM68提高了基于缺失值插值的分布精度：现实世界环境调查研究中平均值输入的替代方法

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Wasser T.; Eisenberg D.;
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年度 2014
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1. Imputation of non-genotyped individuals based on genotyped relatives: assessing the imputation accuracy of a real case scenario in dairy cattle [J] . Aniek C Bouwman, John M Hickey, Mario PL Calus, Genetics, selection, evolution . 2014,第1期

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3. Multiple Statistical Imputation of Missing Data in a Real World Clinical Cohort Increased Sample Size and Power with Minimal Deviations Enhancing the Clinical Research Potential of the Observational Dataset [J] . Tatangelo Mark, Li Xiuying, Cesta Angela, The Journal of rheumatology . 2017,第6期

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4. Missing value imputation techniques depth survey and an imputation Algorithm to improve the efficiency of imputation [C] . Thirukumaran S., Sumathi A. Fourth International Conference on Advanced Computing. . 2012

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5. Planned Missing Data Designs for Causal Inference in Large Surveys: Design and Imputation [D] . Su, Dan. 2019

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6. Imputation of non-genotyped individuals based on genotyped relatives: assessing the imputation accuracy of a real case scenario in dairy cattle [O] . Aniek C Bouwman, John M Hickey, Mario PL Calus, 2014

机译：基于基因型亲属的非基因型个体的估算：评估奶牛真实案例中的估算准确性
7. Increased Accuracy of Distribution Based Missing Value Imputation: An Alternative to Mean Imputation in Real World Environment Survey Research [O] . Thomas Wasser 2014

机译：基于分布的缺失价值估算提高了准确性：现实世界环境调查研究中的替代算法

PRM68 Increased Accuracy of Distribution Based Missing Value Imputation: An Alternative to Mean Inputation in Real World Environment Survey Research

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