Employing Propensity Score Techniques
In this chapter, we’ll familiarize ourselves with the concept of propensity scores, something we touched on lightly in Chapters 2 and 3. It’s a vital tool for identifying confounding variables in causal inference. To be specific, propensity scores help to clear the mist in knowing which variables need conditioning by balancing confounding variables between groups of data. This methodology has power in transforming observational studies so that they resemble randomized trials, a kind of statistical practice that’s crucial for solid causal conclusions.
In addition to learning new theory, we will also be getting our hands dirty with R code. We’ll walk through techniques such as matching, stratification, and weighting – each of which has a unique flair. We’ll also practice our theory with real-life examples, turning abstract concepts into concrete skills. By the end of this chapter, you won’t just...
