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Why do I get extremely large ranges using the imputeData() function in mclust package in R?


Error in function Mclust() in package mclustBigrquery cannot coerce integersSubset xts file by dateR - mice - adding a column that sums columns with imputed valuesR package development: testthat fails because of not verified subfunction in Mclust packageScraping table from web linkhow to use scale and dist with a dataset with column nameunable to install mclust package R in ubuntugetting error in mclust-package while working on univariate fitError when running cluster analysis using mclust function in R






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0















original.dat <- read_sav(file ="N219.sav")
View(original.dat)

imp.dat <- imputeData(original.dat[,-(129:165)])
View(imp.dat)


I still get an imputed dataset, it's just that the ranges for an item on a 4pt or 7pt Likert scale get -22 to +35 or even 1 to 1900. I also receive the following warning message:




In mix::prelim.mix(data[, ord], p = sum(categorical)) : NAs
introduced by coercion to integer range











share|improve this question






























    0















    original.dat <- read_sav(file ="N219.sav")
    View(original.dat)

    imp.dat <- imputeData(original.dat[,-(129:165)])
    View(imp.dat)


    I still get an imputed dataset, it's just that the ranges for an item on a 4pt or 7pt Likert scale get -22 to +35 or even 1 to 1900. I also receive the following warning message:




    In mix::prelim.mix(data[, ord], p = sum(categorical)) : NAs
    introduced by coercion to integer range











    share|improve this question


























      0












      0








      0








      original.dat <- read_sav(file ="N219.sav")
      View(original.dat)

      imp.dat <- imputeData(original.dat[,-(129:165)])
      View(imp.dat)


      I still get an imputed dataset, it's just that the ranges for an item on a 4pt or 7pt Likert scale get -22 to +35 or even 1 to 1900. I also receive the following warning message:




      In mix::prelim.mix(data[, ord], p = sum(categorical)) : NAs
      introduced by coercion to integer range











      share|improve this question
















      original.dat <- read_sav(file ="N219.sav")
      View(original.dat)

      imp.dat <- imputeData(original.dat[,-(129:165)])
      View(imp.dat)


      I still get an imputed dataset, it's just that the ranges for an item on a 4pt or 7pt Likert scale get -22 to +35 or even 1 to 1900. I also receive the following warning message:




      In mix::prelim.mix(data[, ord], p = sum(categorical)) : NAs
      introduced by coercion to integer range








      r missing-data imputation r-haven mclust






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 22 at 5:10









      jacky_learns_to_code

      5032721




      5032721










      asked Mar 22 at 1:01









      do92do92

      12




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