Search Results - "Multiple imputation (Statistics)"

Estimating Poverty in Afghanistan Without Consumption Data: An Imputation-Based Approach.

Authors: Barriga-Cabanillas, Oscar Chawla, Parth Redaelli, Silvia et al.

Source: Journal of Development Studies. Jul2026, Vol. 62 Issue 7, p1126-1147. 22p.

Applying machine learning-based multiple imputation methods to nonparametric multiple comparisons in longitudinal clinical studies.

Authors: Yanarateş, Tuncay Karabulut, Erdem

Source: Journal of Biopharmaceutical Statistics. May2026, Vol. 36 Issue 3, p549-560. 12p.

A multiple imputation approach in enhancing causal inference for overall survival in randomized controlled trials with crossover.

Authors: Zhao, Ruochen Lin, Junjing Xu, Jing et al.

Source: Journal of Biopharmaceutical Statistics. May2026, Vol. 36 Issue 3, p438-455. 18p.

Enhancing data completeness in time series: Imputation strategies for missing data using significant periodically correlated components.

Authors: Ahmad, Asmaa Rose, Eric J. Roy, Michael S. et al.

Source: PLoS ONE. 7/6/2026, Vol. 21 Issue 7, p1-14. 14p.

Multiple Imputation of a Continuous Outcome with Fully Observed Predictors Using TabPFN.

Authors: Sepin, Jerome¹ (AUTHOR)

Source: Stats. Apr2026, Vol. 9 Issue 2, p38. 18p.

Longitudinal Methods Versus Multiple Imputation to Infer Missing Maternal Data in Registry‐Based Pregnancy Studies.

Authors: Sakai, Takamasa Nordeng, Hedvig van Gelder, Marleen M. H. J.

Source: Paediatric & Perinatal Epidemiology. Feb2026, Vol. 40 Issue 2, p264-277. 14p.

A two-stage joint modeling approach for multiple longitudinal markers and time-to-event data.

Authors: Baghfalaki, Taban Hashemi, Reza Helmer, Catherine et al.

Source: Statistical Methods in Medical Research. Feb2026, Vol. 35 Issue 2, p330-345. 16p.

Missing Data in OHCA Registries: How Multiple Imputation Methods Affect Research Conclusions—Paper II.

Authors: Zhan, Stella Jinran Saffari, Seyed Ehsan Ong, Marcus Eng Hock et al.

Source: Journal of Clinical Medicine. Jan2026, Vol. 15 Issue 2, p732. 12p.

Performance of Multiple Imputation Methods for Binary Logistic Regression with Missing Covariates: Simulation Study.

Alternate Title: Açıklayıcı Değişkenlerinde Eksik Gözlem Olan İki Durumlu Lojistik Regresyon İçin Çoklu Atama Yöntemlerinin Performansı: Simülasyon Çalışması.

Authors: YANARATEŞ, Tuncay¹ tuncyanar20008@gmail.com

Source: Turkiye Klinikleri Journal of Biostatistics. 2026, Vol. 18 Issue 1, p27-36. 10p.

Outcome-Assisted Multiple Imputation of Missing Treatments.

Authors: Feldman, Joseph Reiter, Jerome P.

Source: Observational Studies. 2026, Vol. 12 Issue 1, p67-90. 24p.

How Many Plausible Values?

Authors: Jewsbury, Paul A. McCaffrey, Daniel F. Jia, Yue et al.

Source: Journal of Educational Measurement. Dec2025, Vol. 62 Issue 4, p531-558. 28p.

Subject Terms: *Data analysis, Multiple imputation (Statistics), Monte Carlo method, Questionnaires, Latent variables, Statistical power analysis

Company/Entity: National Assessment of Educational Progress (Project)

A Two-Step Variable Selection Strategy for Multiply Imputed Survival Data Using Penalized Cox Models.

Authors: Yang, Qian Luo, Bin Yu, Chenxi et al.

Source: Bioengineering (Basel). Nov2025, Vol. 12 Issue 11, p1278. 29p.

Regression analysis of interval-censored failure time data under semiparametric transformation models with missing covariates.

Authors: Lou, Yichen Du, Mingyue

Source: International Journal of Biostatistics. Nov2025, Vol. 21 Issue 2, p321-337. 17p.

MICE-PSO-RF Model for Predicting Coal Spontaneous Combustion Temperature Based on Multiple Imputation by Chained Equations.

Authors: Zheng, Xuezhao Li, Peihua Cai, Guobin et al.

Source: Combustion Science & Technology. 2026, Vol. 198 Issue 8, p2225-2242. 18p.

Subject Terms: *Multiple imputation (Statistics), *Random forest algorithms, *Coal combustion, *Machine learning, *Particle swarm optimization, *Temperature measurements, *Missing data (Statistics)

Handing missing data using multiple imputation in hybrid control clinical trials with modified power prior.

Authors: Shimada, Sunao Taguri, Masataka

Source: Journal of Biopharmaceutical Statistics. Jun2026, p1-24. 24p. 9 Illustrations.

Multiple Imputation of Missing Data in Moderated Factor Analysis.

Authors: van Ginkel, Joost R Molenaar, Dylan

Source: Multivariate Behavioral Research. May/Jun2026, Vol. 61 Issue 3, p452-468. 17p.

Exploring the Use of Multiple Imputation for Handling Missing Covariates in Meta-Regression with Dependent Effect Sizes.

Authors: Lee, Jihyun Beretvas, S. Natasha Keller, Brian T.

Source: Multivariate Behavioral Research. May2026, p1-25. 25p. 7 Illustrations.

Toward accurate credit evaluation: an efficient imputation approach for financial data.

Authors: Lu, Jie Zhuo, Shengda Qiu, Jinjie et al.

Source: Data Science & Management. Sep2025, Vol. 8 Issue 3, p374-387. 14p.

A data efficient framework for analyzing structural transformation in low and middle income economies.

Authors: Katende, Ronald¹ (AUTHOR) rkatende@kab.ac.ug

Source: Scientific Reports. 10/1/2025, Vol. 15 Issue 1, p1-24. 24p.

A two-stage joint model approach to handle incomplete time dependent markers in survival data through inverse probability weight and multiple imputation.

Authors: Vishwakarma, Gajendra K. Bhattacharjee, Atanu Rajbongshi, Bhrigu Kumar

Source: Scientific Reports. 9/30/2025, Vol. 15 Issue 1, p1-17. 17p.