Time Series, Health & Evidence Synthesis · Biostatistics & Clinical Trials

Computational Biostatistics · Survival Analysis and Time-to-Event Models

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Introduction Computational Biostatistics · Multivariate Analysis

Overview

Topics covered

  • Introduction
  • Survival Analysis Models
  • Fundamentals and Peculiarities of Time-to-Event Data
  • The Nature of Censoring and Truncation
  • Likelihood Formulation under Independent Censoring
  • Non-Parametric Estimation of the Survival Function

Related concepts

Main connections

  • Survival analysis & Kaplan-Meier
  • Maximum likelihood estimation
  • Calculus & differentiation
  • Variance & standard deviation
  • Epidemiological measures & risk ratios
  • Residual analysis & diagnostics

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

S(t)=ℙ(T>t)=1−F(t)=∫t∞f(u)du.
View LaTeX sourceS(t) = \P(T > t) = 1 - F(t) = \int_t^{\infty} f(u) \dd u.