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RE: st:Why fixed effect estimates are different using Stata and SPSS?


From   "Kieran McCaul" <[email protected]>
To   <[email protected]>
Subject   RE: st:Why fixed effect estimates are different using Stata and SPSS?
Date   Wed, 7 Jan 2009 11:21:06 +0900

SPSS is using REML whereas -xtreg- is using ML.
-xtreg- doesn't allow you to use REML, but -xtmixed- does.

______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2140
Fax: (08) 9224 8009
email: [email protected]
http://myprofile.cos.com/mccaul 
http://www.researcherid.com/rid/B-8751-2008
______________________________________________
The fact that no one understands you doesn't make you an artist.

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Mandy fu
Sent: Wednesday, 7 January 2009 9:50 AM
To: [email protected]
Subject: Re: st:Why fixed effect estimates are different using Stata and
SPSS?

Hi Mr. Samuels,

Thanks for  helping out! I really apprecaite it.
Sorry to bother you again . After adding the statement that I forgot,
the SPSS result is still different from Stata. It'll be great if you
could give me some suggestion how to revise the commands to get the
same result as Stata.  Thanks a lot!
Mandy

Here's the command revised:
------------------------------------------SPSS--------------------------
------------------------------------
MIXED lnhr WITH lnwg kids ageh agesq disab
  /FIXED=lnwg kids ageh agesq disab | SSTYPE(3)
 /METHOD=REML
 /RANDOM = INTERCEPT  |  SUBJECT(id)
 /PRINT=SOLUTION.
------------------------------------------------------------------------
-----------------------------------------------------------
95%
Confidence Interval
Parameter	Estimate	Std. Error	df	t	Sig.
Lower Bound      Upper Bound
Intercept	7.208567	.104325	3713.093	69.097	.000
7.004028	7.413106
lnwg	.116703	.013741	2092.169	8.493	.000	.089756	.143650
kids	.004658	.004943	3000.492	.942	.346	-.005035
.014351
ageh	.007799	.005394	3935.455	1.446	.148	-.002777
.018374
agesq	-.000102	6.778785E-53744.521	-1.509	.131	-.000235
3.063344E-5
disab	-.069206	.017256	5231.818	-4.011	.000	-.103034
-.035377
---------------------------------------------------------

On Tue, Jan 6, 2009 at 7:10 PM, Steven Samuels
<[email protected]> wrote:
> The two setups are not comparable.  In your SPSS syntax, you left out
a
> statement like:
> /RANDOM = INTERCEPT | SUBJECT(id)
>
> -Steve
> On Jan 6, 2009, at 7:01 PM, Mandy fu wrote:
>
>>
>>
-----------------------------STATA--------------------------------------
--------------------------------------
>> . xtset id
>> . xtreg lnhr lnwg kids ageh agesq disab,fe
>>
>>
------------------------------------------------------------------------
----------------------------------
>>        lnhr |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
>> Interval]
>>        lnwg |   .1647719   .0189379     8.70   0.000     .1276448
>>  .2018989
>>        kids |  -.0011805   .0062019    -0.19   0.849    -.0133391
>>  .0109781
>>        ageh |   .0142179   .0063804     2.23   0.026     .0017095
>>  .0267263
>>       agesq |  -.0001676   .0000814    -2.06   0.039    -.0003272
>> -8.10e-06
>>       disab |  -.0628007   .0185922    -3.38   0.001      -.09925
>> -.0263514
>>       _cons |   6.945659   .1258117    55.21   0.000      6.69901
>>  7.192308
>> _____________________________________________________________________
>> ----------------------------------SPSS----------------------------
>> MIXED lnhr WITH lnwg kids ageh agesq disab
>>   E(0.000001, ABSOLUTE)
>>  /FIXED=lnwg kids ageh agesq disab | SSTYPE(3)
>>  /METHOD=REML
>>  /PRINT=SOLUTION.
>>
>>
------------------------------------------------------------------------
-------------
>> Parameter Estimate      Std. Error      df      t       Sig.
>> Intercept       7.467766        .083797 5314.000        89.117  .000
>> lnwg    .082290 .009305 5314.000        8.844   .000
>> kids    .007982 .003652 5314.000        2.186   .029
>> ageh    -.000745        .004363 5314.000        -.171   .864
>> agesq   -1.681402E-6    5.407029E-5     5314.000        -.031   .975
>> disab   -.095341        .016312 5314    -5.845  .000
>>
>>
------------------------------------------------------------------------
--------------
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