multiple-mice

问题 I am researching how to use multiple imputation results. The following is my understanding, and please let me know if there're mistakes. Suppose you have a data set with missing values, and you want to conduct a regression analysis. You may perform multiple imputation for m = 5 times, and for each imputed data set (5 imputed data sets now) you run a regression analysis, then "pool" the coefficient estimates from these m = 5 models via Rubin's rules (or use R package "pool"). My question is

问题 I am researching how to use multiple imputation results. The following is my understanding, and please let me know if there're mistakes. Suppose you have a data set with missing values, and you want to conduct a regression analysis. You may perform multiple imputation for m = 5 times, and for each imputed data set (5 imputed data sets now) you run a regression analysis, then "pool" the coefficient estimates from these m = 5 models via Rubin's rules (or use R package "pool"). My question is

问题 I want to run 150 multiple imputations by using mice in R . However, in order to save some computing time, I would lie to subdivide the process in parallel streams (as suggested by Stef van Buuren in "Flexible Imputation for Missing Data"). My question is: how to do that? I can imagine 2 options: opt.1: imp1<-mice(data, m=1, pred=quicktry, maxit=15, seed=1) imp2<-mice(data, m=1, pred=quicktry, maxit=15, seed=1) imp...<-mice(data, m=1, pred=quicktry, maxit=15, seed=1) imp150<-mice(data, m=1,