Natural experiment on the effect of a binary treatment on viewing metrics, where treating units has a cost

data_example_with_cost

Format

A data.table with simulated data from a quasi-experiment (observational study) with five baseline covariates, a single timepoint binary treatment, and a continuous-valued outcome (metric for viewing time). There are 5000 unique units in the dataset, each in a single row, and 8 columns, described below.

id

Numeric ID of the observed unit. No repeated measures.

num_devices

The number of viewing devices recorded for the given user. A possible segmentation covariate.

is_p2plus

TODO: FILL IN. A possible segmentation covariate.

is_newmarket

A binary numeric indicator of whether the user falls in a region corresponding to a new market.

baselin_ltv

TODO:

baseline_viewing

TODO:

treatment

A binary numeric indicator of whether the unit received (non-randomly) the intervention of interest.

outcome_viewing

A continuous-valued measurement of viewing hours, the outcome of interest. Note that this mimics a metric derived from the viewing time, not the time itself.

cost

The cost associated with delivering treatment to the unit.