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st: Computation of Standardized Logistic Parameter - lstand


From   "Emmanuel F. Koku" <[email protected]>
To   "[email protected]" <[email protected]>
Subject   st: Computation of Standardized Logistic Parameter - lstand
Date   Sun, 21 Nov 2004 14:10:11 -0500

Hi,  FYI..

there is fast algorithm   ... "lstand"...that computes beta weights, as well as
unstandardized coeffs and odd rations..it only applies to the logistic command.

/emmanuel
=============================================
Emmanuel F. Koku
[email protected]               
Ph.D Candidate and Research Associate
Centre for Urban and Community Studies
University of Toronto
455 Spadina Avenue
Toronto, Canada M5S 2G8
Tel: 1(443)465-4653
Fax: 1(208)977-0232
========================================


Quoting [email protected]:

 Emmanuel:
 
 Perhaps you can mention to the Statalist that you found the answer in lstand.
 
 For some reason I cannot send a message, or reply, to Statalist.  It may help
 
 others as well.
 
 Thanks, joe Hilbe
 
 
 In a message dated 11/21/2004 11:21:43 AM US Mountain Standard Time, 
 [email protected] writes:
 Joe,
 
 the Lstand did work...I think i was getting no observation error because 
 during
 conversion from spss, stata mistakingly recorded some of my numeric variables
 
 as
 string.  I got an "destring" ado that was able to convert the data to
 numeric
 format, and thereafter, everything worked fine.
 
 I must say, I am very impressed with this program, and wondered why i had 
 stayed
 with sas/spss for so long ... it has tons of features, and the user-produced
 algorithms/extensions is a plus. I'm using version 6 at the moment - my 
 student
 budget cannot afford version 8 at this time, but i can't wait to get a hold
 of
 one and take check it out.
 
 thanks for pointing me to lstand..it does what i wanted, and i've already
 produced my table. One question though about building hierarchical models.. 
 how
 can i check the chi-sq test for the full and restricted models (i.e, if i
 want
 to find out if it would be statistically significant to include a set of
 interaction terms..in a fuller model, do i go by the value of LR chi^2 (df) 
 and
 Prob> chi^2 values printed by the logistic command?
 
 sincerely, Emmanuel
 
 =============================================
 Emmanuel F. Koku
 [email protected]               
 Ph.D Candidate and Research Associate
 Centre for Urban and Community Studies
 University of Toronto
 455 Spadina Avenue
 Toronto, Canada M5S 2G8
 Tel: 1(443)465-4653
 Fax: 1(208)977-0232
 ========================================
 
 
 Quoting [email protected]:
 
 Emmanuel:
 
 I just tried running lstand following a logistic regression. See the output 
 below. It does exactly what I intended.  Perhaps your copy is not good, or
 (the 
 likely reason)  when you copied it there were lines that were too long and 
 got wrapped. These have to be manually corrected.  I'll send you my copy if
 you 
 still have problems. 
 
 Best,  Joe
 
 ========================
 
 .  use auto
 
 .  logistic foreign mpg weight length turn trunk, nolog
 
 Logistic regression                               Number of obs   =        
 74
                                                    LR chi2(5)      =     
 43.42
                                                    Prob > chi2     =    
 0.0000
 Log likelihood = -23.322345                       Pseudo R2       =    
 0.4821
 
 ------------------------------------------------------------------------------
       foreign | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf.
 Interval]
 -------------+----------------------------------------------------------------
           mpg |   .8377264   .0814023    -1.82   0.068     .6924533   
 1.013477
        weight |   .9965262   .0021876    -1.59   0.113     .9922477   
 1.000823
        length |   1.043064   .0714009     0.62   0.538     .9121028    
 1.19283
          turn |    .655959   .1120318    -2.47   0.014     .4693526   
 .9167567
         trunk |   1.011491   .1220834     0.09   0.925     .7984084   
 1.281442
 ------------------------------------------------------------------------------
 
 
 . lstand
 
 Table of Predictor Estimates:
 Standardized Coefficients and Partial Correlations
 
 No.  Var         Coef          OR      St.Coef      PartCorr    Prob(z)
 =======================================================================
 0   Constant  20.8919
 1   mpg       -0.1771      0.8377      -0.5648       -0.1211      0.068
 2   weight    -0.0035      0.9965      -1.4911       -0.0755      0.113
 3   length     0.0422      1.0431       0.5176        0.0000      0.538
 4   turn      -0.4217      0.6560      -1.0227       -0.2132      0.014
 5   trunk      0.0114      1.0115       0.0269        0.0000      0.925
 =======================================================================
 
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