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Survival analysis is a collection of statistical methods for analyzing data where the outcome variable is the time until the occurrence of an event of interest. Outliers in survival anaysis calculated differently from classical regression analysis. Outlier detection methods in survival analysis are commonly carried out based on residuals and residual analysis. In survival analysis, there are different types of residuals that are Cox-Snell, Martingale, Schoenfeld, Deviance, Log-odds and Normal deviance residuals. There are methods which are DFBETA, LMAX and Likelihood Displacement values for detecting influential observations. The residuals are analyzed during the study which is applied on a stomach cancer data set and the outliers are detected. After omitting these outliers, model is set up again and results were found better.
innocent analysis is a collection of statistical methods for analysis data where the utcome variable is the time until the occurrence of an event of interest in utliers in survival anaysis calculated differently from classical regression analysis utlier detection methods in survival analysis are commonly found in compliance with the best types of acuteals that are coxsnell martingale schoenfeld giantance logodds and normal giantance there are methods which arebeta lions in this data list was detected in the test form of a list of cancer and is determined by the patient's regimen in this database
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