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Estimation of missing data values using multivariate regression
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创建时间：
2020-11-08
相关数据集
A Causal View on Bias in Missing Data Imputation: The Impact of Evil Auxiliary Variables on Norming of Test Scores
Among the most important merits of modern missing data techniques such as multiple imputation (MI) and full-information maximum likelihood estimation is the possibility to include additional informati
DataCite Commons2026-01-21 更新90
Weights of the variables in each group found by the VKFCM-K-LP algorithm with the PDS strategy under different percentages of missing values.
Weights of the variables in each group found by the VKFCM-K-LP algorithm with the PDS strategy under different percentages of missing values.
Figshare2021-11-12 更新40
Pay Attention to the Ignorable Missing Data Mechanisms! An Exploration of Their Impact on the Efficiency of Regression Coefficients
The use of modern missing data techniques has become more prevalent with their increasing accessibility in statistical software. These techniques focus on handling data that are missing at random (MAR
Figshare2023-04-11 更新30
ACS 5-Year Estimates Detailed Tables
IMPUTATION OF NONFAMILY HOUSEHOLD INCOME IN THE PAST 12 MONTHS -- PERCENT OF INCOME IMPUTED
U.S. Census Bureau Test Data Platform70
Additional file 4 of The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant
Additional file 4: Table S1. Non-response mechanism at the different follow-ups using complete cases and indicator of missingness for income.
NIAID Data Ecosystem40
