Results 31 to 40 of about 293,301 (286)

An Empirical Comparison of Multiple Imputation Methods for Categorical Data

, 2016
Multiple imputation is a common approach for dealing with missing values in statistical databases. The imputer fills in missing values with draws from predictive models estimated from the observed data, resulting in multiple, completed versions of the ...
Akande, Olanrewaju, Li, Fan, Reiter, Jerome   +2 more
core   +2 more sources

Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness

Journal of Causal Inference, 2020
The problem of missingness in observational data is ubiquitous. When the confounders are missing at random, multiple imputation is commonly used; however, the method requires congeniality conditions for valid inferences, which may not be satisfied when ...
Corder Nathan, Yang Shu
doaj   +1 more source

Missing-Data Handling Methods for Lifelogs-Based Wellness Index Estimation: Comparative Analysis With Panel Data

JMIR Medical Informatics, 2020
BackgroundA lifelogs-based wellness index (LWI) is a function for calculating wellness scores based on health behavior lifelogs (eg, daily walking steps and sleep times collected via a smartwatch).
Kim, Ki-Hun, Kim, Kwang-Jae
doaj   +1 more source

Multiple imputation of maritime search and rescue data at multiple missing patterns.

PLoS ONE, 2021
Based on the missing situation and actual needs of maritime search and rescue data, multiple imputation methods were used to construct complete data sets under different missing patterns.
Guobo Wang, Minglu Ma, Lili Jiang, Fengyun Chen, Liansheng Xu   +4 more
doaj   +1 more source

Missing Data Approaches in eHealth Research: Simulation Study and a Tutorial for Nonmathematically Inclined Researchers

Journal of Medical Internet Research, 2010
BackgroundMissing data is a common nuisance in eHealth research: it is hard to prevent and may invalidate research findings. ObjectiveIn this paper several statistical approaches to data “missingness” are discussed and tested in a simulation ...
Blankers, Matthijs, Koeter, Maarten W J, Schippers, Gerard M   +2 more
doaj   +1 more source

MissForest - nonparametric missing value imputation for mixed-type data

, 2011
Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set.
D. J. Stekhoven, Harley, Kurgan, Latal, LITTLE, Oba, P. Buhlmann, Smit, Troyanskaya, van Buuren, Wille, Wu   +11 more
core   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

Molecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns, Jaclyn S. Long, Sergio Lilla, Kelly Hodge, Marcus J. G. W. Ladds, Colin Nixon, Paula Fernández‐Palanca, Sara Zanivan, Pilar Acedo, Stephen P. Pereira, Kevin M. Ryan   +10 more
wiley   +1 more source

A Comparative Study on Missing Value Imputation Techniques in Machine Learning [PDF]

SHS Web of Conferences
Handling missing values is a crucial step in data preprocessing, as incomplete data can significantly impact model performance and overall data integrity.
Meng Haoyu
doaj   +1 more source

Multiple imputation of multiple multi-item scales when a full imputation model is infeasible [PDF]

, 2016
Background Missing data in a large scale survey presents major challenges. We focus on performing multiple imputation by chained equations when data contain multiple incomplete multi-item scales.
Morris, TP
core   +1 more source

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source