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Re: st: Reshape with prefix using a varlist
From
Richard Murphy <[email protected]>
To
[email protected]
Subject
Re: st: Reshape with prefix using a varlist
Date
Mon, 14 Mar 2011 18:25:29 -0700
The label "country1-country244" represents the remaining 244
variables, containing the total amount of students from that country
at that level in a uni-year.
Are you suggesting something along the lines of?
foreach x in varlist var1-var244{
egen ug_`x'=total(`x') if LEVEL==UG
egen pg_`x'=total(`x') if LEVEL==PG
}
Richard
On 14 March 2011 18:21, Richard Murphy <[email protected]> wrote:
> The label "country1-country244" represents the remaining 244
> variables, containing the total amount of students from that country
> at that level in a uni-year.
> Are you suggesting something along the lines of
> foreach x in varlist eu uk {
>
>The label "country1-country244" represents the remaining 244
variables, containing the total amount of students from that country
at that level in a uni-year.
Are you suggesting something along the lines of
foreach x in varlist eu uk {
> On 14 March 2011 18:02, Nick Cox <[email protected]> wrote:
>> Thanks. That clarifies some things but not others. In your example,
>> you have 7 headings but 6 columns of data. What is
>> "country1-country244"? A variable label?
>>
>> The totals for groups are easily computable using -egen, total()- with
>> your present structure.
>>
>> On Tue, Mar 15, 2011 at 12:45 AM, Richard Murphy
>> <[email protected]> wrote:
>>> Hi Nick ,
>>> I appreciate that it looks foolish making a wide dataset even wider,
>>> but I don't think its that bad in this case.
>>> I have university by degree level by year data. For each of these i
>>> have the number of students coming from 244 different countries, along
>>> with total EU and total OS.
>>>
>>> year instit LEVEL os uk eu country1-country244
>>> 1994 1 ug 12 146 0
>>> 1994 1 pgr 3 335 3
>>> 1994 1 pgt 1 101 0
>>> 1995 1 ug 7 119 0
>>> 1995 1 pgr 4 300 9
>>> 1995 1 pgt 6 59 17
>>>
>>> There are 3 levels of degree, which i would like to make wide. So that
>>> I would have a panel dataset for universities over time. The reason
>>> why i want to do this is that I want to calculate the cross
>>> subsidisation that occurs between the degree levels, and for this I
>>> need the totals for each within an observation.
>>>
>>> I need to do this for all the countries as i'm using a Card
>>> Shift-Share approach as an instrument for changes in overseas numbers,
>>> which i would like to define in various different ways throughout the
>>> analysis (EU, NonEU, Asia, ect).
>>>
>>> And i would like the prefix, so that the variable names fit into my
>>> pre existing do files for the analysis.
>>>
>>> Best regards
>>> Richard
>>>
>>>
>>> On 14 March 2011 17:24, Nick Cox <[email protected]> wrote:
>>>> Please tell us directly more about your dataset and why you think
>>>> -reshape wide- is a good idea. From what you say it just make most
>>>> analyses more difficult. Also, how many variables will you end up
>>>> with?
>>>>
>>>> Nick
>>>>
>>>> On Tue, Mar 15, 2011 at 12:13 AM, Richard Murphy
>>>> <[email protected]> wrote:
>>>>> Hi all,
>>>>> I want to reshape long data to wide, putting the 'j' string variable
>>>>> at the begging of the stub.
>>>>> This would be fine if I have a limited number of variables as i can
>>>>> just use the @ function.
>>>>> reshape wide @var1 @var2 @var3 @var4, i(instit year) j(LEVEL) string
>>>>>
>>>>> But this does not work if i use the variable list functionality of
>>>>> reshape. I would like to know if their is an easier way of doing this,
>>>>> rather than typing in all 244 variables preceded by @.
>>>>> reshape wide @var1-@var244, i(instit year) j(LEVEL) string
>>>>>
>>
>> *
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>>
>
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