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Re: st: limitations of "generate" with missing data


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: limitations of "generate" with missing data
Date   Mon, 11 Apr 2011 23:19:51 +0100

Add ) at end in #3.

On Mon, Apr 11, 2011 at 11:15 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> The underlying problem can be illustrated by sorting. Suppose we
> -sort- a variable, which contains missings, in numeric order. Where do
> the missings go? We need a decision: either missing is regarded as
> larger than any non-missing, or smaller than any non-missing. Stata
> made the first decision.
>
> Any way, here are some solutions:
>
> gen myvar1 =  (gread_comp_score_pcnt>.79) if gread_comp_pcnt < .
>
> gen myvar2 =  (gread_comp_score_pcnt>.79) if !missing(gread_comp_pcnt)
>
> gen myvar3 = cond(missing(gread_comp_pcnt), ., (gread_comp_score_pcnt > .79)
>
> gen myvar4 = (gread_comp_score_pcnt > .79) / (!missing(gread_comp_pcnt))
>
> (5. don't throw away information by turning a measure into an indicator!)
>
> Nick
>
> On Mon, Apr 11, 2011 at 11:01 PM, Michael Costello
> <michaelavcostello@gmail.com> wrote:
>> Statalisters,
>>
>> I recently ran into a problem with the following dataset:
>>
>> . tab  gread_comp_score_pcnt, m
>> gread_comp_ |
>>  score_pcnt |      Freq.     Percent        Cum.
>> ------------+-----------------------------------
>>          0 |        150        7.50        7.50
>>         .2 |         85        4.25       11.75
>>         .4 |         97        4.85       16.60
>>         .6 |         82        4.10       20.70
>>         .8 |         72        3.60       24.30
>>          1 |         15        0.75       25.05
>>          . |      1,499       74.95      100.00
>> ------------+-----------------------------------
>>      Total |      2,000      100.00
>>
>> The high number of "missing" is by design, a by-product of a
>> horizontally structured dataset that I have yet to rectify.
>>
>> When I run the command:
>> gen gread_comp_score_pcnt80= (gread_comp_score_pcnt>.79)
>> I am left with
>>
>> . tab  gread_comp_score_pcnt80, m
>> gread_comp_ |
>> score_pcnt8 |
>>          0 |      Freq.     Percent        Cum.
>> ------------+-----------------------------------
>>          0 |        414       20.70       20.70
>>          1 |      1,586       79.30      100.00
>> ------------+-----------------------------------
>>      Total |      2,000      100.00
>>
>> As you can see, the 87 values above .79 were set to 1, but so were all
>> the missing values!!  I have toyed with the code a bit, trying
>> variations such as
>> . gen gread_comp_score_pcnt80= (gread_comp_score_pcnt>.79 &
>> gread_comp_score_pcnt!=.)
>> but that converts all the missing to 0's, which is only marginally better.
>>
>> So the question is, is there some way to use a single, precise line of
>> code to create eighty-seven 1's, four hundred fourteen  0's and 1499
>> Missing values in one dummy variable?  I know I can do it with several
>> lines of code, but I'm looking for something more concise, as it needs
>> to run many hundreds of times.
>>
>

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