Possible issue with _get_counts and _get_tc_counts

[shaddyab]

Given 100K (N=1e5) samples with the following distribution:
Treatment = 98% (W=1)
Control = 2% (W=0)
Hence p = 0.98

The samples were balanced for response such that, for response (Y=1), the samples are split 1% (W=0, Y=1) Control vs 49% (W=1, Y=1) Treatment. Similarly, for no response (Y=0), the samples are split 1% (W=0, Y=0) Control vs 49% (W=1, Y=0) Treatment.

Based on this I would expect the two functions _get_counts and _get_tc_counts in pylift.eval to return the following values.
Nt1o1 = 49K, Nt0o1 = 1K , Nt1o0 = 49K, Nt0o0 = 1K
Nt1 = 98K, Nt0 = 2K , N = 1e5

However, the functions are returning the following values instead

Nt1o1 = 25K, Nt0o1 = 25K, Nt1o0 = 25K, Nt0o0 = 25K
Nt1 = 50K, Nt0 = 50K , N = 1e5

Could it be that that the implemented logic which is based on summing 1/p and 1/(1-p) values need to be modify?

[rsyi]

Hey @shaddyab -- this is working as intended, but the documentation is outdated. These functions are meant to calculate the effective counts, scaled by the propensity p, not the raw counts. The documentation though is indeed incorrect, so I'll update that.

[rsyi]

PR here: #8