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Practical Predictive Analytics by Ralph Winters

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Comparing the models

Even though the survival curves are similar, we can see that at the end of 12 months, 56% of the customers were retained, as opposed to the original 27%. We could attribute that to the intervention that took place at month 6.

Use the summary(survfit) function to compare the modes:

> summary(survfit(CoxModel.2))

Call: survfit(formula = CoxModel.2)

v

time n.risk n.event survival std.err lower 95% CI upper 95% CI

1 1488 15 0.994 0.00157 0.991 0.997

2 1455 52 0.973 0.00359 0.966 0.980

3 1393 34 0.958 0.00461 0.949 0.967

4 1342 20 0.950 0.00518 0.940 0.960

5 1315 39 0.932 0.00624 0.920 0.945

6 1245 42 0.913 0.00736 0.898 0.927

7 1156 24 0.898 0.00801 0.883 0.914

8 1020 32 0.877 0.00902 0.859 0.895

9 850 40 0.846 0.01052 ...

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