Kaplan-Meier survival analysis

Kaplan-Meier survival analysis

Summary of Kaplan-Meier survival analysis

The Kaplan-Meier survival analysis is used to demonstrate survival over a certain amount of time. It is used in trials to show the effect of an intervention.

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Kaplan-Meier survival analysis

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$Chapter 9 Biostatistics & Epidemiology: Non-parametric Tests KAPLAN-MEIER SURVIVAL ANALYSIS osms.it/Kaplan-Meier_survival_analysis ▪ Estimates survival from lifetime data; measures fraction of survivors over treatment time; simplest method of computing survival over time ▫ Plot of percent survival versus time; generated from status at last observation, time to event ▫ Large sample size → approaches population effect ▫ Accounts for censored data; withdrawn from study, lost to follow-up; alive at last follow-up (i.e. right-censoring—data above a certain value, but otherwise unknown) ▫ Limited capacity to estimate survival adjusted for covariates KAPPA COEFFICIENT osms.it/kappa-coefficient ▪ AKA Cohen’s kappa coefﬁcient ▪ Measure of inter-rater agreement ▪ Compares ability of different raters to classify categorical variables ▪ Interobserver agreement: accounts for agreement that occurs by chance, when raters measure same thing, using same observation method ▪ Calculated from observed, expected frequencies from diagonal of contingency table ▪ If kappa = 1 ▫ Agreement is perfect ▪ If kappa = 0 ▫ Agreement is no better than if agreement happened by chance ▪ Example for interpreting agreement based on kappa coefﬁcient ▫ None: < 0 ▫ Fair: 0.20–0.40 ▫ Moderate: 0.40–0.60 ▫ Good: 0.60–0.80 ▫ Very good: 0.80–1.00 MANN-WHITNEY U TEST osms.it/Mann-Whitney_u_test ▪ Nonparametric test equivalent to unpaired t-test ▪ Compares differences between two unpaired groups that are not normally distributed ▫ Uses number ranks rather than raw data ▫ Provides p-value indicating whether or not groups are signiﬁcantly different from each other (p < 0.05; unlikely to happen by chance) OSMOSIS.ORG 63$

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Kaplan-Meier survival analysis

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