Clinical Research: Bias, Randomization and Blinding

Introduction

What this guide covers

A rigorous mathematical, causal and methodological approach for the mitigation of systematic error and the validation of causal inference in controlled clinical trials.

Overview

Topics covered

• Introduction
• Epistemological Framework of Causal Inference in Medicine
• The Rubin Potential Outcomes Model (Rubin Causal Model)
• Taxonomy and Mathematical Formalization of Bias
• 2.1 Selection Bias
• 2.2 Information Bias (Measurement Error)

Related concepts

Main connections

• Clinical trials & RCT design
• Permutation & exact tests
• Causal inference & potential outcomes
• Confounding & selection bias
• Directed acyclic graphs (DAGs)
• Linear algebra & matrices

Compatible notation

Mathematical sample in LaTeX

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