R 中的 MICE 包：被动插补

Question

I aimed to handle missing values with multiple imputation and then analyse with mixed linear model.

I am stacked by passive imputation for "BMI" (body mass index) and "BMI category". "BMI" was calculated by height and weight and then categorized into "BMI category".

How to impute 'BMI category'?

The database looks like below:

 sub_eu_surf[1:5, 3:12]

    age gender smoking exercise education sbp dbp height weight      bmi
    1  41      1       1        2        18 120  80    185    107 31.26370
    2  46      1       3        2        18 130  70    182    102 30.79338
    3  46      1       3        2        18 130  70    182    102 30.79338
    4  47      1       1        2        14 130  80    178     78 24.61810
    5  47      1       1        1        14 150  80    175     85 27.75510

Since 'bmi category' is not a predictor of my imputation, I decided to create it after imputation. And details are below:
1. To define method and predictor

ini<-mice(sub_eu_surf, maxit=0)
meth<-ini$meth
meth["bmi"]<-"~I(weight/(height/100)^2)"

pred <- ini$predictorMatrix
pred[c("pm25_global", "pm25_eu", "pm10_eu", "no2_eu"),  ]<-0 
pred[,c("bmi", "hba1c", "pm25_eu", "pm10_eu")]<-0
pred[,"tc"]<-0
pred[c("smoking", "exercise", "hdl", "glucose"), "tc"]<-1
pred[c("smoking", "exercise", "hdl", "glucose"), "ldl"]<-0
vis <- ini$vis
imp_eu<-mice(sub_eu_surf, meth=meth, pred=pred, vis=vis, seed=200, print=F, m=5, maxit=5)
long_eu<- complete(imp_eu, "long", include=TRUE)
long_eu$bmi_category<-cut(as.numeric(long_eu$bmi), breaks=c(0, 18.5, 25, 30, 72))
complete_eu<-as.mids(long_eu)

But I received an error when analyzing my data:

    test1<-with(imp_eu, lme(sbp~pm25_global+gender+age+education+bmi_category, random=~1|centre))
    Error in eval(expr, envir, enclos) : object 'bmi_category' not found

How does this happen?

Answer 1

You are running your analyses on the original mids object imp_eu , not on the modified complete_eu . Try:

test1<-with(complete_eu, lme(sbp~pm25_global+gender+age+education+bmi_category, random=~1|centre))