I studied the Hernan/Robins book for a course on causal inference, and I love it. But frankly it's a pretty niche topic, and so for the non-statisticians here o

I studied the Hernan/Robins book for a course on causal inference, and I love it. But frankly it's a pretty niche topic, and so for the non-statisticians here on HN who are trying to get better at statistics, just keep in mind that there are so many other topics you probably want to tackle first. Many of the concerns addressed in the Hernan/Robins book probably wouldn't even make sense to you if you didn't have a firm statistical background already. Gelman/Hill's Data Analysis Using Regression and Multilevel/Hierarchical Models or Angrist/Pischke's Mastering 'Metrics embed ideas and techniques from causal inference into the broader context of regression modeling which makes these books more immediately useful. Those would probably be my two recommendations for non-statisticians.