Causal questions
- The heart of causal analysis is the causal question.
- It dictates data analysis, methods, and target populations.
Goals of data analysis
Causal questions are part of a broader set of questions we can ask with statistical techniques related to the primary tasks of data science:
description
prediction
causal inference
Goals of data analysis
- The goal is often muddled by both the techniques we use (regression, for instance, is helpful for all three tasks) and the way we talk about them.
- When researchers are interested in causal inference from non-randomized data, we often use euphemistic language like “association” instead of declaring our intent to estimate a causal effect
Schrödinger’s Causality
- “Associate” most common root word for effects.
- Only 1% used “cause.”
- Action recommendations in 33% of studies.
- Stronger action recommendations than implied by effect description.
- Only 4% used formal causal models.