I applied Amelia II to multiply impute missings in our survey data. I used AmeliaView and the imputation was successful, so Amelia generated five sets of multiply imputed data in Stata (dta) format (that I had chosen). 

After the multiple imputation I conducted a few sets of regression analyses using "Clarify" to combine the results across the five multiply imputed data. The analyses also worked well,the coefficients all make sense (they correspond with the other analyses we have done using "observed" data) but a problem is some of the analyses sometimes yielded exceptionally high degrees of freedom for some variables.  I don't know why I got this inflated degrees of freedom because all procedures went well without any error messages (not every variables but some of the variables included yielded high degrees of freedom). For your information, I didn't have any other problems other than this.

With regard to this, I emailed to Matt and was advised to use Zelig for data analysis (and I will try to do that) but still wonder about these generally high degrees of freedom issue.

I attached the some of the results from our analysis below (sorry about very-long variable name, it tracks our record of changes), so if any of you can give us any reasons for this, it will be greatly appreciated !!!

Thanks a lot!

 

Ologit estimates (via multiple imputation)          Nobs = 1274

 

---------------------------------------------------------------

Academic_Rank |      Coef.   Std. Err.       t         d.f.    P>|t|

---------+-----------------------------------------------------

female~g |  -.3274721    .166179     -1.971         46    0.055

Minori~g |  -.2167513   .2327173     -0.931         21    0.362

Marrie~d |   .1626777   .2992682      0.544         13    0.596

childr~g |  -.0014547   .0611694     -0.024       1369    0.981

Partne~e |   .1729933   .1713316      1.010         66    0.316

Progra~d |   .0937531   .0533029      1.759        737    0.079

YearsT~b |  -.1231956   .0332016     -3.711        326    0.000

Q18Sp~1a |   -.031667   .0363591     -0.871        140    0.385

Overa~se |    .255504   .1046298      2.442        391    0.015

  Q24a_1 |   .3497809   .0661697      5.286        107    0.000

Joint_~g |    .240031   .2157427      1.113        884    0.266

Privat~g |   .1729383   .1528752      1.131       1393    0.258

PHD_pr~g |  -.4210008   .2339427     -1.800        450    0.073

MA_pro~g |  -.5302672   .1984522     -2.672        228    0.008

Curren~k |   .0081537   .0687515      0.119        962    0.906

Overa~ce |   .0831138   .0275379      3.018        227    0.003

Releas~g |   .1378443   .0192077      7.177       8560    0.000

     Age |   .1728987   .0092188     18.755        107    0.000

   _cut1 |   7.459078   .5828492     12.798        175    0.000

   _cut2 |   9.781068   .6282563     15.569        175    0.000

---------------------------------------------------------------

 

Number of simulations  : 1000

Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 b15 b16 b17 b18 b19 b20

Datasets used for MI   : Amelia_07081 Amelia_07082 Amelia_07083 Amelia_07084 Amelia_07085