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Re: st: RE: counting number of new cases in every year


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: RE: counting number of new cases in every year
Date   Thu, 10 May 2012 19:43:42 +0100

Key correction:

_n == 1 | (_freq > 0 & _freq[_n-1] == 0)

should be

_freq > 0 & (_n == 1 | _freq[_n-1] == 0)

Nick

On Thu, May 10, 2012 at 6:15 PM, Nick Cox <[email protected]> wrote:
> I can't make sense of your -reshape-. Your structure is already -long- and there is just one variable that is -P*-. As it is, the -reshape- command is illegal in the context you give. It seems quite unneeded, so I start afresh.
>
> I first read in your dataset.
>
> . input      Year str1  P
>
>          Year          P
>  1.  1995   A
>  2.  1995   B
>  3.  1995   A
>  4.  1995   C
>  5.  1995   D
>  6.  1995   A
>  7.  1995   E
>  8.  1995   A
>  9.  1996   B
>  10.  1996   A
>  11.  1996   A
>  12.  1996   M
>  13.  1996   A
>  14.  1996   H
>  15.  1996   A
>  16.  1996   C
>  17. end
>
> Then we reduce the dataset to a set of counts.
>
> . contract Year P , zero
>
> . l
>
>     +------------------+
>     | Year   P   _freq |
>     |------------------|
>  1. | 1995   A       4 |
>  2. | 1995   B       1 |
>  3. | 1995   C       1 |
>  4. | 1995   D       1 |
>  5. | 1995   E       1 |
>     |------------------|
>  6. | 1995   H       0 |
>  7. | 1995   M       0 |
>  8. | 1996   A       4 |
>  9. | 1996   B       1 |
>  10. | 1996   C       1 |
>     |------------------|
>  11. | 1996   D       0 |
>  12. | 1996   E       0 |
>  13. | 1996   H       1 |
>  14. | 1996   M       1 |
>     +------------------+
>
> Then a -P- is new if it wasn't observed the previous year. Notice that I define "new" as including the first time any value of -P- is observed.
>
> . bysort P (Y) : gen new =  _n == 1 | (_freq > 0 & _freq[_n-1] == 0)
>
> . l
>
>     +------------------------+
>     | Year   P   _freq   new |
>     |------------------------|
>  1. | 1995   A       4     1 |
>  2. | 1996   A       4     0 |
>  3. | 1995   B       1     1 |
>  4. | 1996   B       1     0 |
>  5. | 1995   C       1     1 |
>     |------------------------|
>  6. | 1996   C       1     0 |
>  7. | 1995   D       1     1 |
>  8. | 1996   D       0     0 |
>  9. | 1995   E       1     1 |
>  10. | 1996   E       0     0 |
>     |------------------------|
>  11. | 1995   H       0     1 |
>  12. | 1996   H       1     1 |
>  13. | 1995   M       0     1 |
>  14. | 1996   M       1     1 |
>     +------------------------+
>
> Then we count how many new categories there are each year.
>
> . tab Y if new
>
>       Year |      Freq.     Percent        Cum.
> ------------+-----------------------------------
>       1995 |          7       77.78       77.78
>       1996 |          2       22.22      100.00
> ------------+-----------------------------------
>      Total |          9      100.00
>
> The generalization to include -Company- should be something like this, but I didn't test it.
>
> contract Company Year P , zero
> bysort Company P (Y) : gen new =  _n == 1 | (_freq > 0 & _freq[_n-1] == 0)
> tab Company Y if new
>
> Nick
> [email protected]
>
> Navid Asgari
>
> I have a dataset which looks like this:
>
>
>      Year   P |
>     |----------|
>  1. | 1995   A |
>  2. | 1995   B |
>  3. | 1995   A |
>  4. | 1995   C |
>  5. | 1995   D |
>     |----------|
>  6. | 1995   A |
>  7. | 1995   E |
>  8. | 1995   A |
>  9. | 1996   B |
>  10. | 1996   A |
>     |----------|
>  11. | 1996   A |
>  12. | 1996   M |
>  13. | 1996   A |
>  14. | 1996   H |
>  15. | 1996   A |
>     |----------|
>  16. | 1996   C
>
> I use the following to count number of new values under variable "P" that exists in the year 1996, but not 1995:
>
> gen id = _n
>> reshape long P , i(id)
>> bysort P (Year id) : gen seq = _n
>
> Count if Year==1996 & seq==1
>
> Now I want to do the same thing for more than 2 successive years (e.g. 1993,1994,1995,1996). So, values of variable "P" in every year will be compared with the value of its previous year (1994 to 1993, then 1995 to 1994, and so forth....
>
> The complexity of this lies in the fact that this comparison has to be done by each unique value of another variable and the starting year and ending year varies in each group. In fact this is how the structure of the real data looks like:
>
>
>     | Year   P    company |
>     |---------------------|
>  1. | 1995   A   Company1 |
>  2. | 1995   B   Company1 |
>  3. | 1995   A   Company1 |
>  4. | 1995   C   Company1 |
>  5. | 1995   D   Company1 |
>     |---------------------|
>  6. | 1995   A   Company1 |
>  7. | 1995   E   Company1 |
>  8. | 1995   A   Company1 |
>  9. | 1996   B   Company1 |
>  10. | 1996   A   Company1 |
>     |---------------------|
>  11. | 1996   A   Company1 |
>  12. | 1996   M   Company1 |
>  13. | 1996   A   Company1 |
>  14. | 1996   H   Company1 |
>  15. | 1996   A   Company1 |
>     |---------------------|
>  16. | 1996   C   Company1 |
>  17. | 1993   G   Company2 |
>  18. | 1993   G   Company2 |
>  19. | 1993   M   Company2 |
>  20. | 1993   K   Company2 |
>     |---------------------|
>  21. | 1993   A   Company2 |
>  22. | 1993   B   Company2 |
>  23. | 1994   C   Company2 |
>  24. | 1994   M   Company2 |
>  25. | 1994   K   Company2 |
>     |---------------------|
>  26. | 1994   L   Company2 |
>     +---------------------+
>
> So for every group under variable company the code will count number of new values of variable "P" in every year that did not exist a year before...

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