Computational Biostatistics — Causal Inference and Computational Clinical Trials

Introduction

What this guide covers

Introduction Chart from the original guide Introduction Advanced Computational Biostatistics

Overview

Topics covered

• Introduction
• Causal Inference and In Silico Tests
• Introduction and Causal Inference Paradigms
• Pearl's Causal Hierarchy
• Directed Acyclic Graphs (DAGs) and Causal Graph Theory
• Elemental d-Separation Structures

Related concepts

Main connections

• Causal inference & potential outcomes
• Bayes' theorem & priors
• Clinical trials & RCT design
• Calculus & differentiation
• Permutation & exact tests
• Directed acyclic graphs (DAGs)

Compatible notation

Mathematical sample in LaTeX

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