Table 2.
Results (λ, CV error, CV-AUC and the set of selected predictors) of the LASSO analyses for each multiply imputed dataset, using two strategies to select λ. In the last column, variables that are consistently selected are highlighted in bold font. See Appendix A for a description of the variables.
| Strategy for selecting λ | MI dataset | λ (scaled) | CV error | CV-AUC | Selected candidate predictors |
|---|---|---|---|---|---|
| Minimum CV error | 1 | 0.239 | 0.142–0.145 | 0.643–0.675 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.inet, CTE.gcptrials_dep, PEC.proc, CEPA.comm_approv, CEPA.exec_30d. |
| 2 | 0.229 | 0.143–0.145 | 0.632–0.668 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.medhsp, CTE.gcptrials_dep, PEC.stmed, CEPA.comm_approv, CEPA.exec_30d. | |
| 3 | 0.313 | 0.145–0.148 | 0.611–0.647 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.smo. | |
| 4 | 0.235 | 0.142–0.145 | 0.645–0.669 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, CTE.gcptrials_dep, PEC.proc, PEC.stmed, PEC.patpop, RPS.chartrev, RPS.promote, RPS.alterncontact, CEPA.comm_approv, CEPA.exec_30d. | |
| 5 | 0.235 | 0.144–0.146 | 0.626–0.675 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.pi_inv, GCC.medhsp, PEC.stmed, CEPA.comm_approv. | |
| 6 | 0.236 | 0.144–0.146 | 0.630–0.662 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.inet, GCC.pi_spec, GCC.medhsp, SA.resnurse, CTE.audit, PEC.proc, PEC.stmed, CEPA.comm_approv, CEPA.exec_30d. | |
| 7 | 0.239 | 0.144–0.146 | 0.624–0.650 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, CTE.audit, CTE.gcptrials_dep, CTE.gcpyrs_stcoord, PEC.stmed, CEPA.comm_approv, CEPA.exec_30d. | |
| 8 | 0.247 | 0.143–0.146 | 0.625–0.664 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.medhsp, SA.recrspec, CTE.audit, CTE.gcpyrs_stcoord, PEC.stmed, PEC.patpop, CEPA.comm_approv, CEPA.exec_30d. | |
| 9 | 0.231 | 0.143–0.146 | 0.626–0.656 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, GCC.inet, GCC.medhsp, GCC.smo, CTE.audit, CTE.gcptrials_dep, PEC.stmed, RPS.chartrev, RPS.alterncontact, CEPA.comm_approv. | |
| 10 | 0.262 | 0.144–0.147 | 0.628–0.660 | (Intercept), GCC.region, GCC.clinic, CTE.distrials_dep, PPC.num12m, PEC.scrfail, RPS.recr_target, RPS.recr_dur, RPS.webcasts, CTE.gcptrials_dep, PEC.stmed, PEC.patpop, RPS.chartrev, CEPA.comm_approv. | |
| 1-SE rule | 1 | 1 | 0.149–0.150 | 0.484–0.507a | (Intercept) |
| 2 | 1 | 0.149–0.150 | 0.483–0.505a | (Intercept) | |
| 3 | 1 | 0.149–0.150 | 0.484–0.504a | (Intercept) | |
| 4 | 1 | 0.149–0.150 | 0.490–0.506a | (Intercept) | |
| 5 | 1 | 0.149–0.150 | 0.484–0.504a | (Intercept) | |
| 6 | 1 | 0.149–0.150 | 0.476–0.503a | (Intercept) | |
| 7 | 1 | 0.149–0.150 | 0.486–0.502a | (Intercept) | |
| 8 | 1 | 0.149–0.150 | 0.488–0.502a | (Intercept) | |
| 9 | 1 | 0.149–0.150 | 0.484–0.500a | (Intercept) | |
| 10 | 1 | 0.149–0.150 | 0.492–0.501a | (Intercept) | |
a
Note that some variability in the results is possible because the maximum value of λ in the CV training sets may not be identical to the maximum value in the complete data.