Cargando…

Imputation of missing values of tumour stage in population-based cancer registration

BACKGROUND: Missing data on tumour stage information is a common problem in population-based cancer registries. Statistical analyses on the level of tumour stage may be biased, if no adequate method for handling of missing data is applied. In order to determine a useful way to treat missing data on...

Descripción completa

Detalles Bibliográficos
Autores principales:	Eisemann, Nora, Waldmann, Annika, Katalinic, Alexander
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2011
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3184281/ https://www.ncbi.nlm.nih.gov/pubmed/21929796 http://dx.doi.org/10.1186/1471-2288-11-129

Ejemplares similares

The ProCaSP study: quality of life outcomes of prostate cancer patients after radiotherapy or radical prostatectomy in a cohort study
por: Eisemann, Nora, et al.
Publicado: (2015)

Normative Data of the EORTC QLQ-C30 For the German Population: A Population-Based Survey
por: Waldmann, Annika, et al.
Publicado: (2013)

Missing value imputation for epistatic MAPs
por: Ryan, Colm, et al.
Publicado: (2010)

Temporal trends in age- and stage-specific incidence of colorectal adenocarcinomas in Germany
por: Waldmann, Annika, et al.
Publicado: (2023)

Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
por: Liao, Serena G, et al.
Publicado: (2014)

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

The importance of batch sensitization in missing value imputation
por: Hui, Harvard Wai Hann, et al.
Publicado: (2023)

Shrinkage regression-based methods for microarray missing value imputation
por: Wang, Hsiuying, et al.
Publicado: (2013)

Advanced methods for missing values imputation based on similarity learning
por: Fouad, Khaled M., et al.
Publicado: (2021)

The population-based oncological health care study OVIS – recruitment of the patients and analysis of the non-participants
por: Pritzkuleit, Ron, et al.
Publicado: (2008)

Population-Based Clinical Cancer Registration in Germany
por: Katalinic, Alexander, et al.
Publicado: (2023)

Robust imputation method for missing values in microarray data
por: Yoon, Dankyu, et al.
Publicado: (2007)

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data
por: Wei, Runmin, et al.
Publicado: (2018)

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets
por: Huang, Min-Wei, et al.
Publicado: (2018)

Imputation of missing genotypes: an empirical evaluation of IMPUTE
por: Zhao, Zhenming, et al.
Publicado: (2008)

Interval cancers after skin cancer screening: incidence, tumour characteristics and risk factors for cutaneous melanoma
por: Hübner, J, et al.
Publicado: (2017)

A hybrid imputation approach for microarray missing value estimation
por: Li, Huihui, et al.
Publicado: (2015)

A Workflow for Missing Values Imputation of Untargeted Metabolomics Data
por: Faquih, Tariq, et al.
Publicado: (2020)

Imputation of missing values for electronic health record laboratory data
por: Li, Jiang, et al.
Publicado: (2021)

Optimization methods for the imputation of missing values in Educational Institutions Data
por: Aureli, D., et al.
Publicado: (2021)

Real-time imputation of missing predictor values in clinical practice
por: Nijman, Steven W J, et al.
Publicado: (2020)

Missing value imputation in proximity extension assay-based targeted proteomics data
por: Lenz, Michael, et al.
Publicado: (2020)

NMF-Based Approach for Missing Values Imputation of Mass Spectrometry Metabolomics Data
por: Xu, Jingjing, et al.
Publicado: (2021)

Missing Value Imputation Method for Multiclass Matrix Data Based on Closed Itemset
por: Tada, Mayu, et al.
Publicado: (2022)

Study results from journals with a higher impact factor are closer to “truth”: a meta-epidemiological study
por: Heidenreich, Andreas, et al.
Publicado: (2023)

Skin cancer screening participation and impact on melanoma incidence in Germany – an observational study on incidence trends in regions with and without population-based screening
por: Waldmann, A, et al.
Publicado: (2012)

The Frequency of and Risk Factors for the Use of Bisphosphonates in the Adjuvant Setting of Primary Breast Cancer in Germany
por: Fick, Eva-Maria, et al.
Publicado: (2015)

Flexible imputation of missing data
por: van Buuren, Stef
Publicado: (2018)

Missing Data and Imputation Methods
por: Schober, Patrick, et al.
Publicado: (2020)

Normalization and missing value imputation for label-free LC-MS analysis
por: Karpievitch, Yuliya V, et al.
Publicado: (2012)

The ability of different imputation methods for missing values in mental measurement questionnaires
por: Xu, Xueying, et al.
Publicado: (2020)

Missing value imputation using least squares techniques in contaminated matrices
por: Garcia-Peña, Marisol, et al.
Publicado: (2022)

A Pragmatic Ensemble Strategy for Missing Values Imputation in Health Records
por: Batra, Shivani, et al.
Publicado: (2022)

The impact of imputation quality on machine learning classifiers for datasets with missing values
por: Shadbahr, Tolou, et al.
Publicado: (2023)

Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
por: Zhao, Chen, et al.
Publicado: (2023)

Combining data discretization and missing value imputation for incomplete medical datasets
por: Huang, Min-Wei, et al.
Publicado: (2023)

Long-term Incidence and Mortality Trends for Breast Cancer in Germany
por: Hübner, Joachim, et al.
Publicado: (2020)

Missing value imputation in a data matrix using the regularised singular value decomposition
por: Arciniegas-Alarcón, Sergio, et al.
Publicado: (2023)

Performance Evaluation of Missing-Value Imputation Clustering Based on a Multivariate Gaussian Mixture Model
por: Xiao, Jing, et al.
Publicado: (2016)

Temporal and Spatial Nearest Neighbor Values Based Missing Data Imputation in Wireless Sensor Networks
por: Deng, Yulong, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_7g7bsanjg0blb1chv5thempqek