error with using mice-imputed MI data with sem.mi

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atrs2

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Feb 23, 2019, 11:05:01 PM2/23/19
to lavaan
Hello,

I am using data that has already been imputed using mice but continue to run into the same error seen below:

Error in semTools::runMI(model = HS.model, data = imps, fun = "cfa") : 
  data is not a valid input type: a partially observed data.frame, a list of imputed data.frames, or previous lavaan.mi object.

Specifically, I am unable to use the imputed data that has been defined by this code:
impHS=mice(HolzingerSwineford1939, m=20, seed=123, print=TRUE, to.data.frame=T)
imps=impHS$imputations

I'm sure this is something very simple that I'm missing but unable to find it on my own. Would appreciate ANY help from the group. Thank you in advance!!

HSMiss <- HolzingerSwineford1939[ , c(paste("x", 1:9, sep = ""),"ageyr","agemo","school")]
set.seed(12345)
HSMiss$x5 <- ifelse(HSMiss$x5 <= quantile(HSMiss$x5, .3), NA, HSMiss$x5)
age <- HSMiss$ageyr + HSMiss$agemo/12
HSMiss$x9 <- ifelse(age <= quantile(age, .3), NA, HSMiss$x9)

impHS=mice(HolzingerSwineford1939, m=20, seed=123, print=TRUE, to.data.frame=T)
imps=impHS$imputations

HS.model <- '
  visual  =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed   =~ x7 + x8 + x9
'
out2 <- cfa.mi(HS.model, data = imps)

I get the same error using "sem.mi" in addition to "cfa.mi"

I've tried "mice::complete(impHS, 'all') and this works but it doesn't seem to be the correct way to do this. 

Mark Seeto

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Feb 24, 2019, 1:15:50 AM2/24/19
to lavaan
The problem is that your impHS doesn't have an element called "imputations", so impHS$imputations is nothing. Using impHS$imputations would be correct if impHS was the output of amelia() rather than mice(). As you know, complete(impHS, "all") works, and as far as I know, there is nothing wrong with using it.

Sebastian85

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Feb 24, 2019, 3:01:14 PM2/24/19
to lavaan
Hi,

I have had the same problem. But I have found the solution creating a list. One Member of this group has posted the solution somewhere in this group. So you can try the code below, 

imp<-mice(impHS, m=20)

nImputations <- 20

impList <- list()

for (i in 1:nImputations) {

  impList[[i]] <- complete(imp, action = i)

}


out2 <- cfa.mi(HS.model, data = imp)
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