Re: Multiple Imputation
Posted by
therp on
URL: http://spssx-discussion.165.s1.nabble.com/Multiple-Imputation-tp4994372p5723112.html
Hello Art, thank you for your answer!
I have missing values on both my IVs and DVs. IVs and DVs were
measured in seperate sessions because I'm working on a prediction
model.
The response scale of my IV items is a Likert scale -here I'm
using an established questionnaire for two constructs. I have 3.3%
missing values on the first and 0.4% on the second construct.
Little's test showed that MCAR is present only for one of the
constructs and seperate variance t tests could not be computed on
the other construct because I only had single missing values on
variables in that construct. Not sure what I will do with this
result yet... Some missings are due to a software error (first
construct) and some are random that I can't explain (second
construct).
For the DVs, I constructed behavioral items and the response scale
for almost all of the items is picking between a prejudiced or not
prejudiced alternative [0;1]. Other DV items have a Likert
response scale and some an interval. I understand that I have to
z-tranform the variables before building scales, but since
z-transformation uses the mean of a variable i don't know if i can
do this before imputation.
I have 6.1% missing data total on my DVs and I will drop variables
with more than 10% missings.
Yes, for the DVs I know that some of my variables allowed
nonresponse too easily (that's the 3 i dropped) and some missings
are due to participants abandoning the experiment at the very end,
and some due to technical mistakes.
Yes, I considered CATPCA, but since i have a dataset with mixed
scales i wasn't sure..but I will look into it again, thank you! On
top of that, a CFA might be even more right vor my procedure since
I have a theory behind the item structure...either way, if I built
scales for my DVs, my missing values would lead to up to 1/3
missing values on my new scales.
Do you think that a better procedure in my case would be running a
CFA with the missing values, build scales, and then impute
missings on scale level?
Thank you very very much for any further advice!
regards,
therp
Am 16.11.2013 18:06, schrieb Art Kendall [via SPSSX Discussion]:
You say you are
building scales. What is the response scale on the
items you are considering? Usually scales are built of strictly
interval level items (e.g., Z's or temperature) or of items that
are not severely discrepant from interval level such as extent
response scales or Likert response scales.
How extensive is your missing data? Do you know why data is
missing for some items?
Were you thinking of CATPCA rather than FACTOR for EFA?
Art Kendall
Social Research Consultants
On 11/16/2013 10:28 AM, therp [via SPSSX Discussion] wrote:
Hello!
Thank you so much for this interesting discussion. Unforunately
as far as I understand the suggestions on using EM for EFA don't
solve the problems for categorical variables with missing
values, since EM cannot be applied to categorical data in SPSS
(and in general??). On top of that, SPSS won't compute Little's
MCAR test for categoriacal variables
Does someone have any suggestions for dealing with missing
values on categorical variables? My proximal goal is to build
scales using EFA and reliability analyses. I know MI is the
state of the art, but as it has already been noted, spss doesn't
produce pooled results for EFA yet.
I appreciate any help/advice/comment!!!!
Art
Kendall
Social Research Consultants