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st: [renamed] Factor Analysis and Missing Data


From   Michael Norman Mitchell <Michael.Norman.Mitchell@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: [renamed] Factor Analysis and Missing Data
Date   Mon, 01 Feb 2010 21:26:08 -0800

Dear Jet

I know this is the StataList, but I would like to suggest a possible fourth option. To consider Mplus, which can use the EM algorithm to obtain estimates on all observations without the need for imputation.

 You can see an example EFA from the UCLA web site at

http://www.ats.ucla.edu/stat/mplus/seminars/introMplus_part1/efa_52.htm

and if you wanted to try Mplus out for yourself, you can download a free demo version at

http://www.statmodel.com/demo.shtml

 Forgive the discussion of non-Stata packages.

Best regards,

Michael N. Mitchell
See the Stata tidbit of the week at...
http://www.MichaelNormanMitchell.com
Visit me on Facebook at...
http://www.facebook.com/MichaelNormanMitchell


Jet wrote:
Hi, dear all,
      I have a question regarding the treatment of missing values in
factor analysis. I have 20 items for factor analysis, but some items
have missing values. If I ignore them, then the Stata treats
respondents with any missing values as missing, and the sample size
will
decrease significantly. So, there are three options. Would appreciate
any suggestions on which option or options I shall follow:
      1. Use the item mean of the nonmissing cases to substitute the
missing value, and then conduct the factor analysis, and calculate the
factor score.
      2. Use multiple imputations to impute the value for each item
with missing values ( But what variables should be used to imputation?
)
      2. Use  the items without missing values to calculate factor
score, and then impute the missing factor score( But what variables
should be used for imputing the factor score?).

     Thank you very much!

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