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Re: st: Re: prvalue with many dummy variables
From
"Vitorino, Maria Ana" <[email protected]>
To
"<[email protected]>" <[email protected]>
Subject
Re: st: Re: prvalue with many dummy variables
Date
Mon, 12 Mar 2012 00:50:25 +0000
Dear Eric,
Thanks so much for the help!
Ana
On Mar 11, 2012, at 11:32 AM, Eric Booth wrote:
> <>
> 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
>>
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/