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Table 3 Bootstrap estimates for each imputed dataset (combination estimate in Table 2 is mean value across imputations, standard error follows from Rubins’s rules

From: G-estimation of causal pathways in vocational rehabilitation for adults with psychotic disorders – a secondary analysis of a randomized trial

  COGNt log (PANSSsumt) log (PANSSnegt)
  \( \kern0.75em {\hat{\psi}}_0^{imp,b} \) \( st. error \) \( {\hat{\psi}}_0^{imp,b} \) \( st. error \) \( {\hat{\psi}}_1^{imp,b} \) \( st. error \) \( {\hat{\psi}}_0^{imp,b} \) \( st. error \) \( {\hat{\psi}}_1^{imp,b} \) \( st. error \)
Imputation
1 0.216 0.08 1.839 2.752 −0.294 0.11 3.686 1.901 −0.3 0.086
2 0.207 0.076 −0.151 2.539 −0.194 0.099 3.084 1.791 −0.249 0.076
3 0.212 0.078 2.128 2.687 −0.331 0.11 3.805 1.965 −0.254 0.089
4 0.234 0.078 1.275 2.668 −0.335 0.126 3.704 1.936 −0.317 0.089
5 0.230 0.08 0.057 2.643 −0.245 0.109 2.632 1.897 −0.248 0.081
6 0.245 0.077 2.436 2.894 −0.344 0.128 4.52 2.025 −0.347 0.095
7 0.252 0.077 0.925 2.636 −0.332 0.116 3.055 1.85 −0.266 0.081
8 0.196 0.078 2.233 2.749 −0.326 0.122 4.334 2.078 −0.346 0.097
9 0.237 0.077 1.348 2.778 −0.304 0.122 3.348 1.881 −0.253 0.082
10 0.212 0.076 3.412 2.816 −0.39 0.129 3.735 1.978 −0.297 0.085
ra 0.058 0.178 0.242 0.099 0.226
FMIb 0.055 0.151 0.195 0.09 0.184
  1. a: relative increase in variance due to missingness, b: fraction of missing information