Results 231 to 240 of about 184,759 (266)

IMPUTING MISSING DATA

Journal of the American Academy of Child & Adolescent Psychiatry, 2004
Calvin D, Croy, Douglas K, Novins
openaire   +2 more sources

Imputation and Missing Data

2017
The presence of missing data is a big challenge for statisticians, especially if the distribution of the missing values is not completely random. Analysis performed on datasets with missing data can lead to erroneous conclusions and significant bias in the results.
Amir Momeni, Matthew Pincus, Jenny Libien   +2 more
openaire   +1 more source

An Interactive Data Imputation System

2022
Yangyang Wu, Xiaoye Miao, Yuchen Peng, Lu Chen 0001, Yunjun Gao, Jianwei Yin   +5 more
openaire   +1 more source

Imputation of Missing Data

2011
Below is a subset of data from a smoking cessation study for smokers newly diagnosed with cancer.Patients were assessed for anxiety and depression at baseline using the Hospital Anxiety and Depression Scale (Zigmond and Snaith 1983), at least 7 days before they were hospitalized for surgery.
Yuelin Li, Jonathan Baron
openaire   +1 more source

Imputation of the Missing Data

2013
We may consider the existence of missing observations as unimportant, considering that the risk of misunderstanding is negligible. The surveyor assumes some model that allows adequately explaining the variable of interest. In such cases, we are able to predict the unknown values and to plug them into some estimator.
openaire   +1 more source

[Imputation of missing data].

Nederlands tijdschrift voor geneeskunde, 2013
In medical research missing data are sometimes inevitable. Different missingness mechanisms can be distinguished: (a) missing completely at random; (b) missing by design; (c) missing at random, and (d) missing not at random. If participants with missing data are excluded from statistical analyses, this can lead to biased study results and loss of ...
Ralph C A, Rippe, Martin, den Heijer, Saskia, le Cessie   +2 more
openaire   +1 more source

An Experimental Survey of Missing Data Imputation Algorithms

IEEE Transactions on Knowledge and Data Engineering, 2022
Lu Chen, Xiaoye Miao, Yunjun Gao
exaly  

Missing response data: To impute or not a impute?

Controlled Clinical Trials, 1988
openaire   +1 more source

Deep learning for missing value imputation of continuous data and the effect of data discretization

Knowledge-Based Systems, 2022
Chih-Fong Tsai
exaly  

Comparison of imputation and imputation-free methods for statistical analysis of mass spectrometry data with missing data

Briefings in Bioinformatics, 2022
Sandra Taylor, Kyoungmi Kim, Machelle Wilson   +2 more
exaly