add influence function calculation

[dbackenroth]

calculates influence function for CALRT and returns to user (if user includes an "id" column in input dataset)

[mbannick]

Hi @dbackenroth, thanks for submitting this PR! Could you please add some brief documentation for this in the function?

[dbackenroth]

Hi @mbannick I added in some documentation, please let me know what else I can provide.

[mbannick]

@dbackenroth Thanks for adding documentation explaining this PR!

If someone has a covariate that is named id (that would be a strange name for a covariate, but it's possible, particularly if they are doing stratification by some type of id), then this may produce unintended behavior. I don't want anything to break for current users since this is a stable package.

Could you make the following change please:

• Modify robincar_logrank so that it takes a return_influence argument that is by default FALSE, and then propagate that argument to model and then it can be accessed here and below, as if model$return_influence rather than if "id" %in% ...? This way, users won't see any change in behavior based on default usage.

[mbannick]

@dbackenroth it also looks like some tests fail with the current PR. Could you please ensure the test suite runs through successfully? Thanks! See e.g., https://github.com/mbannick/RobinCar/actions/runs/20396466576/job/58744492353?pr=37.

[dbackenroth]

@mbannick hi, i added in unit tests. two of the tests are failing for me but I don't think that has to do with my code (test-glm-calibration.R: test calibration and test-glm-legacy.R: GLM legacy), it's related to functions not being found, e.g., str_detect. I added in two columns to robincar_tte signature, one is return_influence and the other is id_col. i may have gone overboard with the error checking, please let me know if you'd like me to make any further changes