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

Advanced Biostatistics · Complex Models and Special Topics

Public introduction · full guide in Eikos

Introduction

What this guide covers

Contemporary biomedical research faces data structures of unprecedented complexity. Longitudinal study designs, the presence of censored observations or competing risks, high-dimensional genomic profiles, and the unavoidable need to draw causal inferences from observational records demand mathematical tools of a rigorous standard.

Overview

Topics covered

  • Introduction
  • Complex models and causal inference
  • Advanced survival models and fragility
  • Rigorous formulation and limits of proportionality
  • Frailty models (Frailty Models)
  • Accelerated Failure Time (AFT) Models

Related concepts

Main connections

  • Survival analysis & Kaplan-Meier
  • Causal inference & potential outcomes
  • Multiple testing & FWER/FDR
  • Variance & standard deviation
  • Mixed & multilevel models (GLMM)
  • Linear algebra & matrices

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