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Cross-Validated Bagged Prediction of Survival
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Sandra E. Sinisi
Published/Copyright:
May 1, 2006
In this article, we show how to apply our previously proposed Deletion/Substitution/Addition algorithm in the context of right-censoring for the prediction of survival. Furthermore, we introduce how to incorporate bagging into the algorithm to obtain a cross-validated bagged estimator. The method is used for predicting the survival time of patients with diffuse large B-cell lymphoma based on gene expression variables.
Keywords: bootstrap aggregating; censoring; cross-validation; diffuse large-B-cell lymphoma; D/S/A algorithm
Published Online: 2006-5-1
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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- Treatment of Uninformative Families in Mean Allele Sharing Tests for Linkage
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- A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting
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- Using Complexity for the Estimation of Bayesian Networks
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- Validation in Genomics: CpG Island Methylation Revisited
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- Letter to the Editor
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Keywords for this article
bootstrap aggregating;
censoring;
cross-validation;
diffuse large-B-cell lymphoma;
D/S/A algorithm
Articles in the same Issue
- Article
- Low-Order Conditional Independence Graphs for Inferring Genetic Networks
- A Generalized Clustering Problem, with Application to DNA Microarrays
- A Bayes Regression Approach to Array-CGH Data
- Statistical Selection of Maintenance Genes for Normalization of Gene Expressions
- Predicting the Strongest Domain-Domain Contact in Interacting Protein Pairs
- Dimension Reduction for Classification with Gene Expression Microarray Data
- A New Type of Stochastic Dependence Revealed in Gene Expression Data
- A New Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity
- Quality Optimised Analysis of General Paired Microarray Experiments
- Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data
- Cross-Validated Bagged Prediction of Survival
- Treatment of Uninformative Families in Mean Allele Sharing Tests for Linkage
- Quantile-Function Based Null Distribution in Resampling Based Multiple Testing
- Combining Results of Microarray Experiments: A Rank Aggregation Approach
- Model Selection for Mixtures of Mutagenetic Trees
- Pseudo-likelihood for Non-reversible Nucleotide Substitution Models with Neighbour Dependent Rates
- A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting
- Bayesian Hierarchical Model for Correcting Signal Saturation in Microarrays Using Pixel Intensities
- Using Complexity for the Estimation of Bayesian Networks
- Detecting Local High-Scoring Segments: a First-Stage Approach for Genome-Wide Association Studies
- Examining Protein Structure and Similarities by Spectral Analysis Technique
- Parameter Estimation for the Exponential-Normal Convolution Model for Background Correction of Affymetrix GeneChip Data
- Approximate Sample Size Calculations with Microarray Data: An Illustration
- Numerical Solutions for Patterns Statistics on Markov Chains
- A Heuristic Bayesian Method for Segmenting DNA Sequence Alignments and Detecting Evidence for Recombination and Gene Conversion
- A Two-Step Multiple Comparison Procedure for a Large Number of Tests and Multiple Treatments
- Validation in Genomics: CpG Island Methylation Revisited
- An Improved Nonparametric Approach for Detecting Differentially Expressed Genes with Replicated Microarray Data
- Letter to the Editor
- Treating Expression Levels of Different Genes as a Sample in Microarray Data Analysis: Is it Worth a Risk?
- Reader's Reaction
- Reader's Reaction to "Dimension Reduction for Classification with Gene Expression Microarray Data" by Dai et al (2006)