Results 31 to 40 of about 199,171 (299)
Multiple Imputation of Missing Data in Educational Production Functions
Computation, 2022 Educational production functions rely mostly on longitudinal data that almost always exhibit missing data. This paper contributes to a number of avenues in the literature on the economics of education and applied statistics by reviewing the theoretical ...
Amira Elasra
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The Indian Journal of Agricultural Sciences, 2023 Occurrence of missing observations in mixture of qualitative and quantitative trait data is a common feature in breeding experiments. However, it becomes difficult to cluster the germplasms in presence of missing data.
RUPAM KUMAR SARKAR +3 more
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The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model
Frontiers in Public Health, 2021 An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values.
Chao-Yu Guo +4 more
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Comparison of regression imputation methods of baseline covariates that predict survival outcomes
Journal of Clinical and Translational Science, 2021 Introduction: Missing data are inevitable in medical research and appropriate handling of missing data is critical for statistical estimation and making inferences.
Nicole Solomon +2 more
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Multiple Imputation to Balance Unbalanced Designs for Two-Way Analysis of Variance
Methodology, 2021 A balanced ANOVA design provides an unambiguous interpretation of the F-tests, and has more power than an unbalanced design. In earlier literature, multiple imputation was proposed to create balance in unbalanced designs, as an alternative to Type-III ...
Joost R. van Ginkel +1 more
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A New Statistic to Evaluate Imputation Reliability
PLoS ONE, 2010 As the amount of data from genome wide association studies grows dramatically, many interesting scientific questions require imputation to combine or expand datasets. However, there are two situations for which imputation has been problematic: (1) polymorphisms with low minor allele frequency (MAF), and (2) datasets where subjects are genotyped on ...
Lin, Peng +11 more
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Evaluation and application of summary statistic imputation to discover new height-associated loci.
PLoS Genetics, 2018 As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis ...
Sina Rüeger +2 more
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Transposable regularized covariance models with an application to missing data imputation [PDF]
, 2010 Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable, meaning that either the rows, columns or both can be treated as features.
Allen, Genevera I., Tibshirani, Robert
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Quality Assessment of Imputations in Administrative Data [PDF]
, 2015 This article contributes a framework for the quality assessment of imputations within a broader structure to evaluate the quality of register-based data.
Astleithner, Franz +5 more
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A Comparative Study of Various Methods for Handling Missing Data in UNSODA
Agriculture, 2021 UNSODA, a free international soil database, is very popular and has been used in many fields. However, missing soil property data have limited the utility of this dataset, especially for data-driven models. Here, three machine learning-based methods, i.e.
Yingpeng Fu, Hongjian Liao, Longlong Lv
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