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Re: st: Re: prvalue with many dummy variables


From   Eric Booth <[email protected]>
To   [email protected]
Subject   Re: st: Re: prvalue with many dummy variables
Date   Sun, 11 Mar 2012 10:32:48 -0500

<>
I agree with Joseph Coveney that -margins- is the way to go.
If you want to stick with -prvalue- (from -spost-), you can 'build' the command in a macro, instead of writing it all out,  with something like:

****************!
forval n = 2/20 {
     loc j  `" `j' school_d`n'=0"'
     }
di `"`j'"'
**
prvalue x(sex=1 age=20 school_d1=1 `j' )
****************!

EAB
__
Eric A. Booth
Public Policy Research Institute 
Texas A&M University
[email protected]
+979.845.6754

On Mar 11, 2012, at 1:35 AM, Joseph Coveney wrote:

> Maria Ana Vitorino wrote:
> 
> If I fit a logit model with many dummy variables such as:
> 
> logit pass sex age school_d*
> 
> where school_d* includes dummies for schools numbered from 1 to 20, i.e.
> school_d1, school_d2, ,,,, school_d20
> 
> how can I calculate a predicted probability without having to specify values for
> all the 19 schools that take value 0?
> 
> For example, suppose I want to do something like
> prvalue x(sex=1 age=20 school_d1=1 school_d2=0 school_d3=0  etc)
> 
> Is there a way of not having to write  in the command line above that
> school_d[i]=0 for every i other than 1?
> 
> --------------------------------------------------------------------------------
> 
> The easiest way would be to use factor variables and -margins-.  It's
> illustrated below.  An alternative that works for older version of Stata is to
> use -lincom- and then transform the linear prediction.  That's also illustrated
> below.  (The first part just creates a fictional dataset to use for
> illustration.)
> 
> Joseph Coveney
> 
> version 11.2
> 
> clear *
> set more off
> set seed `=date("2012-03-10", "YMD")'
> quietly set obs 20
> generate byte school = _n
> generate byte count = 50
> expand count
> generate byte pass = 0.5 < runiform()
> generate byte sex = 0.5 < runiform()
> generate byte age = 18 + floor(4 * runiform())
> logit pass i.sex c.age i.school, nolog
> 
> *
> * Easiest
> *
> margins , at(sex=1 age=20 school=1)
> 
> *
> * Alternative
> *
> quietly lincom _b[_cons] + _b[age] * 20 + _b[1.sex]
> display in smcl as text "Pr(pass | sex == 1 & " ///
>    "age == 20 & school == 1) = " ///
>    as result %05.3f invlogit(r(estimate))
> 
> exit
> 
> 
> *
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*
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