hi list,
I googled this invalid lables issue. It seems different people doing different
analysis encountered this problem. So I guess this is not about the MICE
package.
However, in general, they have categorical variables, in my case, I double
checked, the bulg_1, bulg_2, and bulg_3 are continuous variables that need to
be imputed.
Why the factor() function was used here: Error in factor(x[, type == (-2)],
labels = 1:n.class)
Thank you very much.
Best regards,
ya
·¢¼þÈË£º ya
·¢ËÍʱ¼ä£º 2012-09-19 11:30
ÊÕ¼þÈË£º 32680822
Ö÷Ì⣺ Fw: invalid labels; length 2 should be 1 or 0
Dear list,
I am trying to impute the two level data, I have a question about a warning.
Could you give me some suggestions please? Thank you very much.
Here is my code and output of mice package:
> ini <- mice(try, maxit=0)
> pred=ini$pred
> pred
FAC1_1 FAC2_1 FAC3_1 FAC4_1 FAC5_1 FAC6_1 FAC7_1 FAC8_1 FAC9_1
FAC10_1 ClassSize_1 ClassSize_2 ClassSize_3 intercept TeacherID_1 bulg_1 bulg_2
FAC1_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC2_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC3_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC4_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC5_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC6_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC7_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC8_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC9_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
FAC10_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
ClassSize_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
ClassSize_2 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
ClassSize_3 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
intercept 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
TeacherID_1 1 1 1 1 1 1 1 1 1
1 1 1 1 0 0 0 0
bulg_1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
bulg_2 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
bulg_3 1 1 1 1 1 1 1 1 1
1 1 1 1 0 1 0 0
bulg_3
FAC1_1 0
FAC2_1 0
FAC3_1 0
FAC4_1 0
FAC5_1 0
FAC6_1 0
FAC7_1 0
FAC8_1 0
FAC9_1 0
FAC10_1 0
ClassSize_1 0
ClassSize_2 0
ClassSize_3 0
intercept 0
TeacherID_1 1
bulg_1 0
bulg_2 0
bulg_3 0
> pred["bulg_1",]=c(2,2,2,2,2,2,2,2,2,2,1,0,0,2,-2,0,0,0)
> imp=mice(try,meth=c("","","","","","","","","","","","","","","","2l.norm","2l.norm","2l.norm"),pred=pred,maxit=3)
iter imp variable
1 1 bulg_3Error in factor(x[, type == (-2)], labels = 1:n.class) :
invalid labels; length 2 should be 1 or 0
> class(formi$bulg_1)
[1] "numeric"
> class(formi$bulg_2)
[1] "numeric"
> class(formi$bulg_3)
[1] "numeric"
The TeacherID_1 is the second level ID. bulg_1, bulg_2, and bulg_3 are
continuous variables that need to be imputed. Why the factor() was used for
continuous variables?
Thank you very much.
Best regards,
ya
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