Real World Health Care Data Analysis

Chapter 2: Causal Inference and Comparative Effectiveness: A Foundation

2.1 Introduction

2.2 Causation

2.3 From R.A. Fisher to Modern Causal Inference Analyses

2.3.1 Fisher’s Randomized Experiment

2.3.2 Neyman’s Potential Outcome Notation

2.3.3 Rubin’s Causal Model

2.3.4 Pearl’s Causal Model

2.4 Estimands

2.5 Totality of Evidence: Replication, Exploratory, and Sensitivity Analyses

2.6 Summary

References

2.1 Introduction

In this chapter, we introduce the basic concept of causation and the history and development of causal inference methods including two popular causal frameworks: Rubin’s Causal Model (RCM) and Pearl’s Causal Model (PCM). This includes the core assumptions necessary for standard causal inference analyses, a discussion of estimands, ...