Table 4.
Bias | Std | RMSE | Coverage IC | ||||||
---|---|---|---|---|---|---|---|---|---|
Implementation | Approach | ||||||||
Cor.param. | Crude | 1.180 | 1.937 | 0.146 | 0.198 | 1.189 | 1.947 | 0.000 | 0.000 |
stan | 0.005 | 0.001 | 0.083 | 0.094 | 0.083 | 0.094 | 0.987 | 0.988 | |
IPW | 0.079 | 0.075 | 0.612 | 0.614 | 0.617 | 0.618 | 0.841 | 0.866 | |
match | 0.213 | 0.214 | 0.143 | 0.161 | 0.256 | 0.267 | 0.747 | 0.796 | |
BCM | 0.039 | 0.007 | 0.131 | 0.147 | 0.136 | 0.147 | 0.976 | 0.983 | |
TMLE | 0.006 | 0.002 | 0.102 | 0.118 | 0.102 | 0.118 | 0.951 | 0.959 | |
OW | 0.012 | 0.006 | 0.131 | 0.142 | 0.131 | 0.143 | 0.990 | 0.990 | |
A-OW | 0.006 | 0.003 | 0.096 | 0.107 | 0.096 | 0.107 | 0.948 | 0.959 | |
Inc.param. | stan | −0.121 | −0.039 | 0.098 | 0.113 | 0.155 | 0.120 | 0.785 | 0.928 |
IPW | 0.209 | 0.181 | 0.174 | 0.195 | 0.272 | 0.266 | 0.621 | 0.755 | |
match | 0.132 | 0.118 | 0.121 | 0.136 | 0.179 | 0.180 | 0.799 | 0.869 | |
BCM | 0.091 | 0.045 | 0.119 | 0.136 | 0.149 | 0.143 | 0.887 | 0.940 | |
TMLE | 0.159 | 0.112 | 0.131 | 0.155 | 0.206 | 0.191 | 0.767 | 0.892 | |
OW | 0.117 | 0.099 | 0.109 | 0.118 | 0.160 | 0.154 | 0.812 | 0.865 | |
A-OW | 0.065 | 0.062 | 0.101 | 0.116 | 0.120 | 0.131 | 0.898 | 0.920 | |
M.Learning | stan | 0.005 | 0.014 | 0.090 | 0.105 | 0.090 | 0.106 | 0.938 | 0.940 |
IPW | 0.159 | 0.138 | 0.185 | 0.200 | 0.244 | 0.244 | 0.720 | 0.801 | |
match | 0.124 | 0.111 | 0.122 | 0.138 | 0.174 | 0.177 | 0.819 | 0.875 | |
BCM | 0.010 | 0.008 | 0.118 | 0.135 | 0.119 | 0.136 | 0.953 | 0.956 | |
TMLE | 0.016 | 0.006 | 0.106 | 0.123 | 0.108 | 0.124 | 0.939 | 0.945 | |
OW | 0.080 | 0.067 | 0.110 | 0.121 | 0.136 | 0.138 | 0.893 | 0.912 | |
A-OW | 0.003 | −0.001 | 0.098 | 0.108 | 0.098 | 0.108 | 0.937 | 0.952 |
Note: Cor.param=correct parametric models, Inc.param=incorrect parametric models, M.Learning=machine learning, Crude=Unadjusted, stan=standardization, IPW=inverse probability weighting, match=matching, BCM=bias-corrected matching, TMLE=targeted maximum likelihood, OW=overlap weights, A-OW=augmented overlap weights. *: in 1 replication, the confidence intervals could not be computed.