From: New adaptive lasso approaches for variable selection in automated pharmacovigilance signal detection
Method | Number of | Number of signals | Number of false | FDP | Specificity | Sensitivity |
---|---|---|---|---|---|---|
generated signals | with known status | positive signals | (%) | (%) | (%) | |
(positive or negative) | ||||||
RFET | 249 | 82 | 13 | 15.9 | 93.6 | 51.9 |
lasso-cv | 220 | 79 | 5 | 6.3 | 97.5 | 55.6 |
lasso-bic | 170 | 65 | 5 | 7.7 | 97.5 | 45.1 |
lasso-perm | 158 | 60 | 4 | 6.7 | 98.0 | 42.1 |
CISL | 109 | 48 | 2 | 4.2 | 99.0 | 34.6 |
adapt-cv | 188 | 70 | 5 | 7.1 | 97.5 | 48.9 |
adapt-univ | 179 | 65 | 4 | 6.2 | 98.0 | 45.9 |
adapt-univ-bic | 163 | 61 | 4 | 6.6 | 98.0 | 42.9 |
adapt-bic | 151 | 60 | 4 | 6.7 | 98.0 | 42.1 |
adapt-cisl | 153 | 60 | 2 | 3.3 | 99.0 | 43.6 |
ps-adjust | 209 | 71 | 6 | 8.5 | 97.0 | 48.9 |
ps-mw | 86 | 40 | 0 | 0.0 | 100.0 | 30.1 |
ps-iptw | 49 | 15 | 3 | 20.0 | 98.5 | 9.0 |
ps-iptwT | 260 | 84 | 12 | 14.3 | 94.1 | 54.1 |