require(rms)
#Get a dataset/keep a few columns
load('boys.rda') # originally from mice package
d <- boys[,c("age", "bmi", "reg")]
i <- with(d, is.na(bmi) | is.na(reg))
length(unique(d$age)); length(unique(d$age[! i]))
#sum(is.na(dat$age)) #0
####Models
##1) Complete case
#Set datadist
# dat_naomit <- na.omit(dat)
# dd <- datadist(dat_naomit)
# options(datadist = "dd")
dd <- datadist(d); options(datadist='dd')
#Run model
f <- orm(age ~ bmi + reg, data = d)
#Run a simple contrast
contrast(f, list(bmi = 20), list(bmi = 19))
summary(f, bmi=19:20, est.all=FALSE)
##2) Multiple imputation (default settings)
#Fit imputation model
# imp_mod <- mice(dat, m = 5) #Happens with ‘aregImpute’ as well
#Fit same orm model with imputed datasets
a <- aregImpute(~ age + bmi + reg, data=d, n.impute=5)
g <-
fit.mult.impute(
formula = age ~ bmi + reg,
fitter = orm,
xtrans = a,
data = d
)
dim(vcov(f, regcoef.only=TRUE))
dim(vcov(g, regcoef.only=TRUE))
summary(g, bmi=19:20, est.all=FALSE)
#Try the same contrast
contrast(g, list(bmi = 20), list(bmi = 19)) #Non-conformable dimension for matrix multiplication
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