The rise of multiple imputation: a review of the reporting and implementation of the method in medical research

P Hayati Rezvan, KJ Lee, JA Simpson - BMC medical research …, 2015‏ - Springer
Background Missing data are common in medical research, which can lead to a loss in
statistical power and potentially biased results if not handled appropriately. Multiple …

A unified approach to measurement error and missing data: overview and applications

M Blackwell, J Honaker, G King - Sociological Methods & …, 2017‏ - journals.sagepub.com
Although social scientists devote considerable effort to mitigating measurement error during
data collection, they often ignore the issue during data analysis. And although many …

[HTML][HTML] Handling missing data in clinical research

MW Heymans, JWR Twisk - Journal of clinical epidemiology, 2022‏ - Elsevier
Because missing data are present in almost every study, it is important to handle missing
data properly. First of all, the missing data mechanism should be considered. Missing data …

Plasma proteomics identify biomarkers and pathogenesis of COVID-19

T Shu, W Ning, D Wu, J Xu, Q Han, M Huang, X Zou… - Immunity, 2020‏ - cell.com
Summary The coronavirus disease 2019 (COVID-19) pandemic is a global public health
crisis. However, little is known about the pathogenesis and biomarkers of COVID-19. Here …

Total quality management practices and corporate sustainable development in manufacturing companies: the mediating role of green innovation

B Albloushi, A Alharmoodi, F Jabeen… - Management …, 2023‏ - emerald.com
Purpose Manufacturing firms face increasing pressure to be more “greener” or
environmentally friendly. Drawing upon the sustainable development (SD) theory and …

Comparing the health of non-binary and binary transgender adults in a statewide non-probability sample

SL Reisner, JMW Hughto - PLoS one, 2019‏ - journals.plos.org
Background In the US, non-binary refers to transgender people who have a gender identity
not aligned with their assigned sex at birth, and who identify outside of the traditional male …

A comparison of multiple imputation methods for missing data in longitudinal studies

MH Huque, JB Carlin, JA Simpson, KJ Lee - BMC medical research …, 2018‏ - Springer
Background Multiple imputation (MI) is now widely used to handle missing data in
longitudinal studies. Several MI techniques have been proposed to impute incomplete …

Clinical and bacterial markers of periodontitis and their association with incident all-cause and Alzheimer's disease dementia in a large national survey

MA Beydoun, HA Beydoun, S Hossain… - Journal of …, 2020‏ - journals.sagepub.com
Microbial agents including periodontal pathogens have recently appeared as important
actors in Alzheimer's disease (AD) pathology. We examined associations of clinical …

Best practices for addressing missing data through multiple imputation

AD Woods, D Gerasimova, B Van Dusen… - Infant and Child …, 2024‏ - Wiley Online Library
A common challenge in developmental research is the amount of incomplete and missing
data that occurs from respondents failing to complete tasks or questionnaires, as well as …

[کتاب][B] Flexible imputation of missing data

S Van Buuren, S Van Buuren - 2012‏ - jstatsoft.org
Treatment of missing data is usually included in a section of its own in most textbooks,
presenting best or most convenient practices, based on the methods presented and the …