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Re: st: RE: programatically dropping variables that don't actually vary
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: RE: programatically dropping variables that don't actually vary
Date
Thu, 9 Aug 2012 20:13:07 +0100
for "and" read "&"
On Thu, Aug 9, 2012 at 8:12 PM, Nick Cox <[email protected]> wrote:
> In principle, many variables could have mean 0. A safer test is that
>
> if r(min) == 0 and r(max) == 0
>
> Nick
>
> On Thu, Aug 9, 2012 at 8:03 PM, Sarah Edgington <[email protected]> wrote:
>> Jenn,
>> There are a variety of ways you might want to do this. What I would do is
>> something like the following:
>>
>> foreach var of varlist dummy1-dummyn {
>> sum `var', meanonly
>> if r(mean)==0 {
>> drop `var'
>> }
>> }
>>
>> This cycles through each of your variables (substitute your actual variable
>> list for "dummy1-dummyn"). For reach variable it calculates the mean. The
>> drop statement in the if loop only gets executed if the value stored in
>> r(mean) is 0.
>>
>> -Sarah
>>
>>
>> -----Original Message-----
>> From: [email protected]
>> [mailto:[email protected]] On Behalf Of Earl, Jennifer
>> Suzanne - (jenniferearl)
>> Sent: Thursday, August 09, 2012 11:46 AM
>> To: [email protected]
>> Subject: st: programatically dropping variables that don't actually vary
>>
>> Hi,
>>
>> I am working with a large number of dummy variables and using collapse to
>> create derivative datasets that are the frequencies of 1's for each dummy
>> variable (a couple of hundred through foreach loops). I want to drop any of
>> the dummy variables that never had a 1 (so mean(dummy1)==0, or
>> max(dummy)==0) but it seems that drop only lets you use an if statement to
>> drop observations, but not an if statement to drop variables.
>>
>> My best guess is to use a list means to create a list of the variable names
>> that can be stored in a local and then fed into a drop command, but can't
>> seem to make that work either since I only want the list of variable names
>> that have a mean of 0. Or maybe transpose the dataset, drop then since the
>> variables are now observations, and transpose back? Another solution would
>> be save through StatTansfer and use it's drop constants feature, and then
>> bring the data back in, but there must be an easier way.
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