Re: st: Need help with working across variables

[Nick Cox <njcoxstata@gmail.com>]

One condition is redundant:

gen x = .

forval j = 1/4 {
       replace x = var`j'  if missing(x) & inlist(var`j', 1, 2)
       replace x = .  if  var`j'  != x & var`j' < .
}



On Sun, Feb 10, 2013 at 10:55 AM, Nick Cox <njcoxstata@gmail.com> wrote:
> Corrected version:
>
> gen x = .
>
> forval j = 1/4 {
>       replace x = var`j'  if missing(x) & inlist(var`j', 1, 2)
>       replace x = . if !missing(x, var`j') & var`j'  != x
> }
>
>
>
> On Sun, Feb 10, 2013 at 10:12 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>> Here is another way to do it:
>>
>> gen x = .
>>
>> forval j = 1/4 {
>>      replace x = var`j'  if missing(x) & inlist(var`j', 1, 2)
>>      replace x = . if !missing(x) & var`j'  != x
>> }
>>
>> So, we initialise to missing; change our minds at the first instance
>> of 1 or 2; but change it back again if we see a different value in the
>> same observation.
>>
>> For a review of working rowwise, see
>>
>> SJ-9-1  pr0046  . . . . . . . . . . . . . . . . . . .  Speaking Stata: Rowwise
>>         (help rowsort, rowranks if installed) . . . . . . . . . . .  N. J. Cox
>>         Q1/09   SJ 9(1):137--157
>>         shows how to exploit functions, egen functions, and Mata
>>         for working rowwise; rowsort and rowranks are introduced
>>
>> .pdf at http://www.stata-journal.com/sjpdf.html?articlenum=pr0046
>>
>> Nick
>>
>> On Sun, Feb 10, 2013 at 5:34 AM, Cory Smith <corybsmith@gmail.com> wrote:
>>> Too complicated in my opinion.
>>>
>>> gen x = 0
>>>
>>> egen Vmin = rowmin(var1 - var4)
>>> egen Vmax = rowmax(var1 - var4)
>>>
>>> replace x = 1 if Vmin == 1 & Vmax == 1 & Vmin != .
>>> replace x = 2 if Vmin == 2 & Vmax == 2 & Vmin != .
>>>
>>> Actually, some of the terms in the above are unnecessary but I kept
>>> them in for clarity.
>>>
>>> On Sun, Feb 10, 2013 at 12:27 AM, Alison Connor <alison.connor@gmail.com> wrote:
>>>> Hi Michael,
>>>>
>>>> There might be a more efficient way to do it, but if you have egenmore
>>>> you can do:
>>>>
>>>>  egen x=rall(var1 var2 var3 var4), c(@==1)
>>>>
>>>> This will be 1 if all non-missing variables are 1, and 0 otherwise. If
>>>> you only have two values for your variables, then you can run this
>>>> command again, and then merge the two into a third variable:
>>>>
>>>>  egen x1=rall(var1 var2 var3 var4), c(@==1)
>>>>  egen x2=rall(var1 var2 var3 var4), c(@==2)
>>>>
>>>> gen x=0
>>>> replace x=1 if x1==1
>>>> replace x=2 if x2==1
>>>>
>>>> If you are going to do this for multiple values, then you can create a loop:
>>>>
>>>> gen x=0
>>>> forvalues i=1/2 {
>>>>    egen x`i'=rall(var1 var2 var3 var4), c(@==`i')
>>>>   replace x=`i' if x`i'==1
>>>>   drop x`i'
>>>>  }
>>
>> On Sun, Feb 10, 2013 at 10:41 AM, Michael Stewart
>> <michaelstewartresearch@gmail.com> wrote:
>>
>>>>> Here is my data format and my question:
>>>>> id      var1    var2    var3    var4
>>>>> 1       1       1       1       .
>>>>> 2       1       1       1       1
>>>>> 3       1       2       1       .
>>>>> 4       2       2       2       2
>>>>> 5       1       1       1       1
>>>>> 6       1       2       .       .
>>>>> 7       2       1       2       .
>>>>>
>>>>> I am trying to generate a new variable x =1 if all non missings values
>>>>> for the variables(per observation) are equal to 1 and x =2 if all non
>>>>> missings values for the variables(per observation) are equal to 2. I
>>>>> tried to do foreach loop like
>>>>>
>>>>> gen x=0
>>>>> foreach x in var1 var2 var3 var4{
>>>>> replace x=1 if `x'=1
>>>>> }
>>>>> but it doesnt seem to do the trick
>>>>>
>>>>> I am specifically interested in to change x =1 if all nonmissign
>>>>> values for an observation are equal to one
>>>>> For example: I would like to replace x=1 for id=1 but not for id 3
>>>>> Similarly, I would like to replace x=2 if all nom missing values for
>>>>> an observation are equal to two.
>>>
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