Estimating causal effects with ordinal exposures
Just passing along a quick note from the world of academia; I, along with my adviser from Brown, Dr. Roee Gutman, published our first paper together.
It’s titled ‘Estimating the average treatment effects of nutritional label use using subclassification with regression adjustment,‘ and presents a case study of how to measure the causal effects of an ordinal exposure. The article is currently online in Statistical Methods in Medical Research.
What is the main point of this paper?
Here’s one of my favorite parts, a graph showing the covariates’ bias before and after subclassifying subjects into groups. In this and many other examples, subclassifying is an important tool as it allows for more of an apples-to-apples comparison. Specifically, it only makes…
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