Analyzing Customer Churn – Using “tmerge” to Build Data Sets

If you've ever done churn analysis using cox regression with time-dependent covariates, you know that the hardest part of doing that type of research is building your base data set. You have to divide each customer's lifetime into "chunks" where the changing values of a host of different predictor variables apply. I've coded this in SQL before, and it gets ugly. Fast.

Merge, everybody, merge!

Thankfully, R has a solution for this that makes life significantly more simple. It's the "tmerge" function, and it's in the survival package. Today, we'll walk through how to use it.

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