Results 11 to 20 of about 202,193 (268)

Missing data imputation and corrected statistics for large-scale behavioral databases [PDF]

Behavior Research Methods, 2011
This paper presents a new methodology to solve problems resulting from missing data in large-scale item performance behavioral databases. Useful statistics corrected for missing data are described, and a new method of imputation for missing data is proposed. This methodology is applied to the DLP database recently published by Keuleers et al.
Courrieu, Pierre, Rey, Arnaud
openaire   +8 more sources

Much Ado About Nothing: Multiple Imputation to Balance Unbalanced Designs for Two-Way Analysis of Variance

Methodology, 2020
In earlier literature, multiple imputation was proposed to create balance in unbalanced designs, as an alternative to Type III sum of squares in two-way ANOVA.
Joost R. van Ginkel, Pieter M. Kroonenberg   +1 more
doaj   +1 more source

Optimal method for determining the intraclass correlation coefficients of urinary biomarkers such as dialkylphosphates from imputed data

Environment International, 2022
Urinary biomarkers are commonly used in epidemiological studies as surrogates or indicators of exposure to chemical substances. Evaluating the reliability of a biomarker is highly important because use of an unreliable marker may lead to ...
Yukiko Nishihama, Yonghang Lai, Tomohiko Isobe, Shoji F. Nakayama   +3 more
doaj   +1 more source

Nonparametric statistical inference and imputation for incomplete categorical data [PDF]

Statistics and Its Interface, 2020
9 pages, 2 ...
Wang, Chaojie, Shen, Linghao, Li, Han, Fan, Xiaodan   +3 more
openaire   +2 more sources

When Does Choice of Accuracy Measure Alter Imputation Accuracy Assessments? [PDF]

PLoS ONE, 2015
Imputation, the process of inferring genotypes for untyped variants, is used to identify and refine genetic association findings. Inaccuracies in imputed data can distort the observed association between variants and a disease.
Shelina Ramnarine, Juan Zhang, Li-Shiun Chen, Robert Culverhouse, Weimin Duan, Dana B Hancock, Sarah M Hartz, Eric O Johnson, Emily Olfson, Tae-Hwi Schwantes-An, Nancy L Saccone   +10 more
doaj   +1 more source

DISSCO: direct imputation of summary statistics allowing covariates [PDF]

Bioinformatics, 2015
Abstract Background: Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype ...
Zheng, Xu, Qing, Duan, Song, Yan, Wei, Chen, Mingyao, Li, Ethan, Lange, Yun, Li   +6 more
openaire   +2 more sources

Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics.

PLoS Computational Biology, 2022
Imputing missing values is common practice in label-free quantitative proteomics. Imputation aims at replacing a missing value with a user-defined one.
Marie Chion, Christine Carapito, Frédéric Bertrand   +2 more
doaj   +1 more source

A genotype imputation method for de-identified haplotype reference information by using recurrent neural network.

PLoS Computational Biology, 2020
Genotype imputation estimates the genotypes of unobserved variants using the genotype data of other observed variants based on a collection of haplotypes for thousands of individuals, which is known as a haplotype reference panel.
Kaname Kojima, Shu Tadaka, Fumiki Katsuoka, Gen Tamiya, Masayuki Yamamoto, Kengo Kinoshita   +5 more
doaj   +2 more sources

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
doaj   +1 more source

Performance of clustering procedures for grouping germplasms based on mixture data with missing observations

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, A R RAO, S D WAHI, K V BHAT   +3 more
doaj   +1 more source