Cargando…

Multiple imputation by predictive mean matching in cluster-randomized trials

BACKGROUND: Random effects regression imputation has been recommended for multiple imputation (MI) in cluster randomized trials (CRTs) because it is congenial to analyses that use random effects regression. This method relies heavily on model assumptions and may not be robust to misspecification of...

Descripción completa

Detalles Bibliográficos
Autores principales:	Bailey, Brittney E., Andridge, Rebecca, Shoben, Abigail B.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2020
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106802/ https://www.ncbi.nlm.nih.gov/pubmed/32228491 http://dx.doi.org/10.1186/s12874-020-00948-6

Ejemplares similares

Tuning multiple imputation by predictive mean matching and local residual draws
por: Morris, Tim P, et al.
Publicado: (2014)

Logistic regression vs. predictive mean matching for imputing binary covariates
por: Austin, Peter C, et al.
Publicado: (2023)

The use of multiple imputation (MI) in cluster randomised trials with suspected missing not at random (MNAR) outcome
por: Playle, Rebecca, et al.
Publicado: (2015)

Multiple imputation methods for bivariate outcomes in cluster randomised trials
por: DiazOrdaz, K., et al.
Publicado: (2016)

Imputation strategies for missing binary outcomes in cluster randomized trials
por: Ma, Jinhui, et al.
Publicado: (2011)

Should multiple imputation be the method of choice for handling missing data in randomized trials?
por: Sullivan, Thomas R, et al.
Publicado: (2016)

Standard and reference‐based conditional mean imputation
por: Wolbers, Marcel, et al.
Publicado: (2022)

Meta-analysis of mean differences from randomized trials with nested clustering
por: Walwyn, Rebecca
Publicado: (2013)

Comparison of multiple imputation and other methods for the analysis of imputed genotypes
por: Auer, Paul L., et al.
Publicado: (2023)

Matching in cluster randomized trials using the Goldilocks Approach
por: Sturdevant, S. Gwynn, et al.
Publicado: (2021)

Peer mentor versus teacher delivery of a physical activity program on the effects of BMI and daily activity: protocol of a school-based group randomized controlled trial in Appalachia
por: Smith, Laureen H., et al.
Publicado: (2018)

Multiple imputation of multiple multi-item scales when a full imputation model is infeasible
por: Plumpton, Catrin O., et al.
Publicado: (2016)

Multiple imputation approaches for epoch-level accelerometer data in trials
por: Tackney, Mia S, et al.
Publicado: (2023)

Geographic pair-matching in large-scale cluster randomized trials
por: Arnold, Benjamin F., et al.
Publicado: (2023)

Multiple imputation of missing data under missing at random: including a collider as an auxiliary variable in the imputation model can induce bias
por: Curnow, Elinor, et al.
Publicado: (2023)

Robust single-cell Hi-C clustering by convolution- and random-walk–based imputation
por: Zhou, Jingtian, et al.
Publicado: (2019)

Assessment of Imputation from Low-Pass Sequencing to Predict Merit of Beef Steers
por: Snelling, Warren M., et al.
Publicado: (2020)

Multiple imputation approaches for handling incomplete three‐level data with time‐varying cluster‐memberships
por: Wijesuriya, Rushani, et al.
Publicado: (2022)

ImputEHR: A Visualization Tool of Imputation for the Prediction of Biomedical Data
por: Zhou, Yi-Hui, et al.
Publicado: (2021)

Combining multiple imputation and bootstrap in the analysis of cost‐effectiveness trial data
por: Brand, Jaap, et al.
Publicado: (2018)

Melissa: Bayesian clustering and imputation of single-cell methylomes
por: Kapourani, Chantriolnt-Andreas, et al.
Publicado: (2019)

Plant-ImputeDB: an integrated multiple plant reference panel database for genotype imputation
por: Gao, Yingjie, et al.
Publicado: (2020)

Weighted multiple imputation of ethnicity data that are missing not at random in primary care databases
por: Pham, Tra My, et al.
Publicado: (2017)

Multiple imputation for patient reported outcome measures in randomised controlled trials: advantages and disadvantages of imputing at the item, subscale or composite score level
por: Rombach, Ines, et al.
Publicado: (2018)

Animal-ImputeDB: a comprehensive database with multiple animal reference panels for genotype imputation
por: Yang, Wenqian, et al.
Publicado: (2020)

Overall success rate of a safe and efficacious drug: Results using six phase 1 designs, each followed by standard phase 2 and 3 designs
por: Ruppert, Amy S., et al.
Publicado: (2018)

Model checking in multiple imputation: an overview and case study
por: Nguyen, Cattram D., et al.
Publicado: (2017)

Practical strategies for handling breakdown of multiple imputation procedures
por: Nguyen, Cattram D., et al.
Publicado: (2021)

Evaluation of approaches for multiple imputation of three-level data
por: Wijesuriya, Rushani, et al.
Publicado: (2020)

Multiple imputation for estimating hazard ratios and predictive abilities in case-cohort surveys
por: Marti, Helena, et al.
Publicado: (2012)

Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables()
por: White, Ian R., et al.
Publicado: (2010)

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation
por: Wahl, Simone, et al.
Publicado: (2016)

Prediction of Breast Cancer Survival by Machine Learning Methods: An Application of Multiple Imputation
por: LOTFNEZHAD AFSHAR, Hadi, et al.
Publicado: (2021)

Multiple imputation for cause-specific Cox models: Assessing methods for estimation and prediction
por: Bonneville, Edouard F, et al.
Publicado: (2022)

A pairwise strategy for imputing predictive features when combining multiple datasets
por: Wu, Yujie, et al.
Publicado: (2022)

Imputation of a true endpoint from a surrogate: application to a cluster randomized controlled trial with partial information on the true endpoint
por: Nixon, Richard M, et al.
Publicado: (2003)

Multiple imputation in practice: with examples using IVEware
por: Raghunathan, Trivellore, et al.
Publicado: (2018)

Multiple imputation of missing data using SAS
por: Berglund, Patricia A, et al.
Publicado: (2014)

Combining Multiple Imputation and Inverse-Probability Weighting
por: Seaman, Shaun R, et al.
Publicado: (2012)

Single versus multiple imputation for genotypic data
por: Fridley, Brooke L, et al.
Publicado: (2009)

Cannot write session to /tmp/vufind_sessions/sess_gg8hl5aknj5krd1h8bll019u62