Results 1 to 10 of about 202,193 (268)

Plausible-Value Imputation Statistics for Detecting Item Misfit. [PDF]

Appl Psychol Meas, 2017
When tests consist of a small number of items, the use of latent trait estimates for secondary analyses is problematic. One area in particular where latent trait estimates have been problematic is when testing for item misfit. This article explores the use of plausible-value imputations to lessen the severity of the inherent measurement unreliability ...
Chalmers RP, Ng V.
europepmc   +4 more sources

PRED-LD: efficient imputation of GWAS summary statistics

BMC Bioinformatics
Background Genome-wide association studies have identified connections between genetic variations and diseases, but they only examine a small portion of single nucleotide polymorphisms.
Georgios A. Manios, Aikaterini Michailidi, Panagiota I. Kontou, Pantelis G. Bagos   +3 more
doaj   +3 more sources

New Trends in Evidence-based Statistics: Data Imputation Problems

Статистика України, 2019
The main reasons for omissions are: 1. Exclusion of the subject from the study due to non-compliance with study requirements; 2. The occurrence of an adverse event; 3. Missing result; 4. Lack of registration; 5.
N. V. Kovtun, A.-N. Ya. Fataliieva
doaj   +3 more sources

Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study

JMIR Public Health and Surveillance
BackgroundImmunization Information Systems (IIS) and surveillance data are essential for public health interventions and programming; however, missing data are often a challenge, potentially introducing bias and impacting the accuracy of vaccine coverage
Sara Brown, Ousswa Kudia, Kaye Kleine, Bryndan Kidd, Robert Wines, Nathanael Meckes   +5 more
doaj   +2 more sources

A Comprehensive Approach to Days’ Supply Estimation in a Real-World Prescription Database: Algorithm Development and Validation Study [PDF]

Online Journal of Public Health Informatics
BackgroundFor accurate medication usage statistics and medication adherence calculations, we need to have an accurate days’ supply (DS) for each prescription.
Maria Malk, Kerli Mooses, Marek Oja, Johannes Holm, Hanna Keidong, Nikita Umov, Sirli Tamm, Sulev Reisberg, Jaak Vilo, Raivo Kolde   +9 more
doaj   +2 more sources

Statistical inference with large‐scale trait imputation

Statistics in Medicine, 2023
Recently a nonparametric method called LS‐imputation has been proposed for large‐scale trait imputation based on a GWAS summary dataset and a large set of genotyped individuals. The imputed trait values, along with the genotypes, can be treated as an individual‐level dataset for downstream genetic analyses, including those that cannot be done with GWAS
Jingchen Ren, Wei Pan
openaire   +2 more sources

Informer-WGAN: High Missing Rate Time Series Imputation Based on Adversarial Training and a Self-Attention Mechanism

Algorithms, 2022
Missing observations in time series will distort the data characteristics, change the dataset expectations, high-order distances, and other statistics, and increase the difficulty of data analysis.
Yufan Qian, Limei Tian, Baichen Zhai, Shufan Zhang, Rui Wu   +4 more
doaj   +1 more source

Using machine learning to impute legal status of immigrants in the National Health Interview Survey

MethodsX, 2022
We describe a novel machine learning method of imputing legal status for immigrants using nationally representative survey data from the Survey of Income and Program Participation (SIPP) and the National Health Interview Survey (NHIS). K-nearest Neighbor
Simon A. Ruhnke, Fernando A. Wilson, Jim P. Stimpson   +2 more
doaj   +1 more source

CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017
Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data.
S. Äyrämö, I. Pölönen, M. A. Eskelinen   +2 more
doaj   +1 more source

RAISS: Robust and Accurate imputation from Summary Statistics [PDF]

Bioinformatics, 2018
AbstractMotivationMulti-trait analyses using public summary statistics from genome-wide association studies (GWAS) are becoming increasingly popular. A constraint of multi-trait methods is that they require complete summary data for all traits. While methods for the imputation of summary statistics exist, they lack precision for genetic variants with ...
Julienne, Hanna, Shi, Huwenbo, Pasaniuc, Bogdan, Aschard, Hugues   +3 more
openaire   +6 more sources