Logistic regression for disease classification using microarray data: model selection in a large p and small n case.
Liao, J G
Logistic regression for disease classification using microarray data: model selection in a large p and small n case. [electronic resource] - Bioinformatics (Oxford, England) Aug 2007 - 1945-51 p. digital
Publication Type: Journal Article; Research Support, N.I.H., Extramural
1367-4811
10.1093/bioinformatics/btm287 doi
Algorithms
Biomarkers, Tumor--analysis
Data Interpretation, Statistical
Diagnosis, Computer-Assisted--methods
Humans
Logistic Models
Models, Biological
Neoplasm Proteins--analysis
Neoplasms--classification
Oligonucleotide Array Sequence Analysis--methods
Regression Analysis
Reproducibility of Results
Sample Size
Sensitivity and Specificity
Logistic regression for disease classification using microarray data: model selection in a large p and small n case. [electronic resource] - Bioinformatics (Oxford, England) Aug 2007 - 1945-51 p. digital
Publication Type: Journal Article; Research Support, N.I.H., Extramural
1367-4811
10.1093/bioinformatics/btm287 doi
Algorithms
Biomarkers, Tumor--analysis
Data Interpretation, Statistical
Diagnosis, Computer-Assisted--methods
Humans
Logistic Models
Models, Biological
Neoplasm Proteins--analysis
Neoplasms--classification
Oligonucleotide Array Sequence Analysis--methods
Regression Analysis
Reproducibility of Results
Sample Size
Sensitivity and Specificity