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Re: st: problem with predicted probabilities


From   Witness Chirinda <[email protected]>
To   [email protected]
Subject   Re: st: problem with predicted probabilities
Date   Tue, 4 Feb 2014 07:04:38 +0200

Thanks Nick and Richard for you help!

On Sun, Feb 2, 2014 at 11:23 PM, Richard Williams
<[email protected]> wrote:
> Getting every case classified as 0 (or 1) is not unusual. For relatively
> rare events, the highest predicted probability for every case may be less
> than .5, so every case gets classified as 0. My own experience is that the
> classification table tends not to be that helpful, especially for events
> that are very rare or very common.
>
>
> At 04:58 AM 2/2/2014, Witness Chirinda wrote:
>>
>> Dear Statalist
>> I want to obtain some predicted probabilities after logistic
>> regression, as attached. I want to use the predicted probabilities in
>> my next step instead of observed prevalence since the latter are
>> adjusted for other (socio-demographic) factors.
>> My problem is that the when I run - estat classification- it giving 0s
>> for + classification. I am sure I am doing it the wrong way somewhere.
>> Please see below output. All variables used in the model have been
>> recorded to be binary 1/0
>>
>> Thanks for any help!
>> ------------------
>>
>>
>> . logistic Health_stat  age maried wealth educat  place sex
>>
>> Logistic regression                               Number of obs   =
>> 2339
>>                                                            LR chi2(6)
>>     =      50.61
>>                                                            Prob > chi2
>>     =     0.0000
>> Log likelihood = -996.02516                       Pseudo R2       =
>> 0.0248
>>
>> ------------------------------------------------------------------------------
>>     Health_stat | Odds Ratio   Std. Err.      z    P>|z|     [95%
>> Conf. Interval]
>>
>> -------------+----------------------------------------------------------------
>>     age  | 1.109083   .0342696     3.35   0.001     1.043909    1.178326
>> maried |  1.2134   .1962535     1.20   0.232     .8837556    1.666004
>> Wealth |  1.430957   .1784661     2.87   0.004     1.120641    1.827203
>> educat |  1.670411   .2010455     4.26   0.000     1.319397     2.11481
>> place   |  .9334522   .1223134    -0.53   0.599     .7220318    1.206779
>> sex     |   1.129008   .1324642     1.03   0.301     .8970722    1.420911
>>
>> . estat class
>>
>> Logistic model for poorSRHS
>>               -------- True --------
>> Classified |         D            ~D  |      Total
>> -----------+--------------------------+-----------
>>      +     |         0                 0  |          0
>>       -     |       370          1969  |       2339
>> -----------+--------------------------+-----------
>>    Total   |       370          1969  |       2339
>>
>> Classified + if predicted Pr(D) >= .5
>> True D defined as poorSRHS != 0
>> --------------------------------------------------
>> Sensitivity                     Pr( +| D)    0.00%
>> Specificity                     Pr( -|~D)  100.00%
>> Positive predictive value       Pr( D| +)       .%
>> Negative predictive value       Pr(~D| -)   84.18%
>> --------------------------------------------------
>> False + rate for true ~D        Pr( +|~D)    0.00%
>> False - rate for true D         Pr( -| D)  100.00%
>> False + rate for classified +   Pr(~D| +)       .%
>> False - rate for classified -   Pr( D| -)   15.82%
>> --------------------------------------------------
>> Correctly classified                        84.18%
>> --------------------------------------------------
>> *
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>> *   http://www.ats.ucla.edu/stat/stata/
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> HOME:   (574)289-5227
> EMAIL:  [email protected]
> WWW:    http://www.nd.edu/~rwilliam
>
>
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*
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