Keywords
StatisticsCalibrationEvent (particle physics)Outcome (game theory)MathematicsEconometricsSet (abstract data type)Regression analysisProportional hazards modelComputer science
Related Publications
Imputing missing covariate values for the Cox model
Abstract Multiple imputation is commonly used to impute missing data, and is typically more efficient than complete cases analysis in regression analysis when covariates have mi...
Importance of events per independent variable in proportional hazards regression analysis II. Accuracy and precision of regression estimates
The analytical effect of the number of events per variable (EPV) in a proportional hazards regression analysis was evaluated using Monte Carlo simulation techniques for data fro...
MULTIVARIABLE PROGNOSTIC MODELS: ISSUES IN DEVELOPING MODELS, EVALUATING ASSUMPTIONS AND ADEQUACY, AND MEASURING AND REDUCING ERRORS
Multivariable regression models are powerful tools that are used frequently in studies of clinical outcomes. These models can use a mixture of categorical and continuous variabl...
Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions
Abstract Many survival studies record the times to two or more distinct failures on each subject. The failures may be events of different natures or may be repetitions of the sa...
Overall <i>C</i> as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation
Abstract The assessment of the discrimination ability of a survival analysis model is a problem of considerable theoretical interest and important practical applications. This i...
Publication Info
- Year
- 2003
- Type
- book-chapter
- Pages
- 1-25
- Citations
- 340
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
340
OpenAlex
Cite This
Byung‐Ho Nam,
Ralph B. D’Agostino
(2003).
Evaluation of the Performance of Survival Analysis Models: Discrimination and Calibration Measures.
Handbook of statistics
, 1-25.
https://doi.org/10.1016/s0169-7161(03)23001-7
Identifiers
- DOI
- 10.1016/s0169-7161(03)23001-7