Here's a small sample of my data :
> sample_n(k,20)
A B C D E
1 1.05 2.02 8.27 0.76 1.02
2 1.2 2.28 19.56 0.62 <NA>
3 1.2 2.31 3.45 0.65 1.22
4 <NA> 2.44 6.76 0.68 1.82
5 <NA> 2.24 6.99 0.59 1.37
6 0.87 1.71 3.32 0.64 1.87
7 <NA> 1.77 3.4 0.6 2.13
8 <NA> 2.17 4.13 0.81 1.19
9 <NA> 1.96 4.39 <NA> 1.66
10 1.15 2.28 14.73 0.73 1.57
11 <NA> 1.76 <NA> 0.79 2.66
12 <NA> 1.97 9 0.81 1.38
13 <NA> 2.18 9.32 0.78 0.9
14 <NA> 1.93 2.3 0.78 1.62
15 1.02 2.05 2.81 0.78 1.24
16 0.94 1.77 1.69 0.73 1.83
17 1.17 2.21 14.79 0.66 1.34
18 1.11 2.18 9.41 <NA> 1.32
19 1.35 2.51 20.44 0.76 0.73
20 <NA> 2.37 <NA> 0.74 1.41
I'm trying to impute the missing data using the package mice :
new_df = mice(df, method="cart")
I get the following error :
Error in edit.setup(data, setup, ...) :
`mice` detected constant and/or collinear variables. No predictors were left after their removal.
How can I fix this?
