Cargando…

Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

BACKGROUND: The appropriate handling of missing covariate data in prognostic modelling studies is yet to be conclusively determined. A resampling study was performed to investigate the effects of different missing data methods on the performance of a prognostic model. METHODS: Observed data for 1000...

Descripción completa

Detalles Bibliográficos
Autores principales:	Marshall, Andrea, Altman, Douglas G, Holder, Roger L
Formato:	Texto
Lenguaje:	English
Publicado:	BioMed Central 2010
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3019210/ https://www.ncbi.nlm.nih.gov/pubmed/21194416 http://dx.doi.org/10.1186/1471-2288-10-112

Ejemplares similares

Imputing missing covariate values for the Cox model
por: White, Ian R, et al.
Publicado: (2009)

The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model
por: Guo, Chao-Yu, et al.
Publicado: (2021)

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study
por: Marshall, Andrea, et al.
Publicado: (2010)

Multiple imputation in Cox regression when there are time‐varying effects of covariates
por: Keogh, Ruth H., et al.
Publicado: (2018)

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models
por: Emura, Takeshi, et al.
Publicado: (2012)

Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation
por: Jackson, Dan, et al.
Publicado: (2014)

Generating survival times to simulate Cox proportional hazards models with time-varying covariates
por: Austin, Peter C
Publicado: (2012)

A Bayesian Approach for the Cox Proportional Hazards Model with Covariates Subject to Detection Limit
por: Chen, Qingxia, et al.
Publicado: (2014)

A calibrated Bayesian method for the stratified proportional hazards model with missing covariates
por: Kim, Soyoung, et al.
Publicado: (2022)

Generating Survival Times Using Cox Proportional Hazards Models with Cyclic and Piecewise Time-Varying Covariates
por: Huang, Yunda, et al.
Publicado: (2020)

Bayesian inference for Cox proportional hazard models with partial likelihoods, nonlinear covariate effects and correlated observations
por: Zhang, Ziang, et al.
Publicado: (2022)

Multiple imputation for handling missing outcome data when estimating the relative risk
por: Sullivan, Thomas R., et al.
Publicado: (2017)

Tests for the proportional hazards assumption in the Cox model
por: Reiersølmoen, L, et al.
Publicado: (2001)

Using fractional polynomials and restricted cubic splines to model non‐proportional hazards or time‐varying covariate effects in the Cox regression model
por: Austin, Peter C., et al.
Publicado: (2021)

Evaluation of multiple imputation approaches for handling missing covariate information in a case-cohort study with a binary outcome
por: Middleton, Melissa, et al.
Publicado: (2022)

Comparison of Methods for Handling Missing Covariate Data
por: Johansson, Åsa M., et al.
Publicado: (2013)

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model
por: Austin, Peter C.
Publicado: (2017)

On the Relation between Prediction and Imputation Accuracy under Missing Covariates
por: Ramosaj, Burim, et al.
Publicado: (2022)

Assessing violations of the proportional hazards assumption in Cox regression: does the chosen method matter?
por: Hiller, Louise, et al.
Publicado: (2015)

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines
por: Marshall, Andrea, et al.
Publicado: (2009)

Simulation study - handling missing covariates in the context of external validation
por: Bonnett, Laura J, et al.
Publicado: (2011)

The Use of Multiple Imputation to Handle Missing Data in Secondary Datasets: Suggested Approaches when Missing Data Results from the Survey Structure
por: Jo, Soojung
Publicado: (2022)

On Cox proportional hazards model performance under different sampling schemes
por: Samawi, Hani, et al.
Publicado: (2023)

Multiple Imputation of Missing Covariates in NONMEM and Evaluation of the Method’s Sensitivity to η-Shrinkage
por: Johansson, Åsa M., et al.
Publicado: (2013)

Imputation of missing covariate values in epigenome-wide analysis of DNA methylation data
por: Wu, Chong, et al.
Publicado: (2016)

Multiple imputation for IPD meta‐analysis: allowing for heterogeneity and studies with missing covariates
por: Quartagno, M., et al.
Publicado: (2015)

Some Classes of Logarithmic-Type Imputation Techniques for Handling Missing Data
por: Pandey, Awadhesh K., et al.
Publicado: (2021)

The proportion of missing data should not be used to guide decisions on multiple imputation
por: Madley-Dowd, Paul, et al.
Publicado: (2019)

Improving efficiency of fitting Cox proportional hazards models for time-to-event outcomes in genome-wide association studies (GWAS)
por: Gebski, Val, et al.
Publicado: (2023)

Trend-constrained corrected score for proportional hazards model with covariate measurement error
por: Zhu, Ming, et al.
Publicado: (2015)

Comparison of Cox proportional hazards regression and generalized Cox regression models applied in dementia risk prediction
por: Goerdten, Jantje, et al.
Publicado: (2020)

Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
por: Seaman, Shaun R, et al.
Publicado: (2012)

Novel Harmonic Regularization Approach for Variable Selection in Cox's Proportional Hazards Model
por: Chu, Ge-Jin, et al.
Publicado: (2014)

Quasi-linear Cox proportional hazards model with cross- L(1) penalty
por: Omae, Katsuhiro, et al.
Publicado: (2020)

Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models
por: Li, Lingyu, et al.
Publicado: (2021)

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

Exact Inference for Hardy-Weinberg Proportions with Missing Genotypes: Single and Multiple Imputation
por: Graffelman, Jan, et al.
Publicado: (2015)

Comparing Smoothing Techniques for Fitting the Nonlinear Effect of Covariate in Cox Models
por: Roshani, Daem, et al.
Publicado: (2016)

Confidence bands for multiplicative hazards models: Flexible resampling approaches
por: Dobler, Dennis, et al.
Publicado: (2019)

When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts
por: Jakobsen, Janus Christian, et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_oh9ip37c2tlnfshk1tgitq0dgp