This is a good question Nick. As explained in my first email, _x_ is
like a fixed variable e.g., gender of the individual. Other variables
can be thought as follows:
y: training programs attended; z duration of the traning program
v: wages received in the last two jobs
Many thanks!
On Mon, Apr 13, 2009 at 4:28 AM, Nick Cox <[email protected]> wrote:
> How do you know that x is 4 for id == 1 in Data 1? That is not clear to me.
>
> Nick
> [email protected]
>
> Quang Nguyen
>
> Thanks Nick and Martin. Actually, the question is a bit trickier than
> "append" can handle. The structure of data 1 and 2 are different,
> thus, the append would result in all missing values for the mitsmatch
> variables. Thus,
>
> append using data2
>
> will result in all missing values for x, y, z in the combined data set.
>
>
> Actually, I would like to have the combined data as follows:
>
> Combined data:
>
> id x y z v
> 1 4 a 7 missing
> 1 4 b 8 missing
> 1 4 c 9 missing
> 1 4 missing missing 4
> 1 4 missing missing 2
>
>
>
> Given:
>
> Data 1
> id v
> 1 4
> 1 2
> 2 6
> 2 7
> -------------
>
> Data 2:
> id x y z
> 1 4 a 7
> 1 4 b 8
> 1 4 c 9
> 2 6 a 7
> 2 6 b 8
> 2 6 c 9
>
>
>
>
> On Mon, Apr 13, 2009 at 3:43 AM, Quang Nguyen <[email protected]> wrote:
>> Dear All:
>>
>> Suppose I have the 2 following data set1:
>>
>> Data 1
>> id v
>> 1 4
>> 1 2
>> 2 6
>> 2 7
>> -------------
>>
>> Data 2:
>> id x y z
>> 1 4 a 7
>> 1 4 b 8
>> 1 4 c 9
>> 2 6 a 7
>> 2 6 b 8
>> 2 6 c 9
>>
>>
>> Note that _x_ is a fixed effect in data 2 as well as the combined data
>> set. Given that, do you know how I can append data 1 to data 2 so
>> that the combined data set will have infor from both data 1 and 2 and
>> some missing values due to mismatch between v and (y,z). Specifically,
>> the combined data for the first observation looks like the following:
>>
>> Combined data:
>>
>> id x y z v
>> 1 4 a 7 mis
>> 1 4 b 8 mis
>> 1 4 c 9 mis
>> 1 4 mis mis 4
>> 1 4 mis mis 2
>> ......
>
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