st: reshape with j split

[David Airey <david.airey@vanderbilt.edu>]

I have a reshape question. I find this one of the hardest commands to 
remember how to use.

I cannot find a help example that exactly parallels my situation. I 
have an identifier that is split between variables. This situation is 
common in ANOVA where treatment cells may be identified by more than 
one factor.

I have data like:

. list, sep(6)

     +----------------------------------------+
     | s1level   s1s2de~y   animal   s2peak~e |
     |----------------------------------------|
  1. |       0         50   1_1_0F     773.75 |
  2. |       0        100   1_1_0F    1001.63 |
  3. |      75         50   1_1_0F      472.5 |
  4. |      75        100   1_1_0F    927.875 |
  5. |      85         50   1_1_0F    611.375 |
  6. |      85        100   1_1_0F    654.375 |
     |----------------------------------------|
  7. |       0         50   1_1_1F    1116.88 |
  8. |       0        100   1_1_1F    1101.38 |
  9. |      75         50   1_1_1F    544.875 |
 10. |      75        100   1_1_1F    567.875 |
 11. |      85         50   1_1_1F    443.875 |
 12. |      85        100   1_1_1F        466 |
     |----------------------------------------|
 13. |       0         50   1_1_2F      309.5 |
 14. |       0        100   1_1_2F    336.286 |
 15. |      75         50   1_1_2F    442.625 |
etc.

where the first two variables s1level and s1s2delay define 6 treatment 
conditions from which s2peakvalue was measured fore each animal. I 
would like to reshape this data to calculate a ratio from the 
conditions within each animal. I would like to get a data set that 
looks like:

animal s2peak0_50 s2peak0_100 s2peak75_50 s2peak75_100 s2peak85_50 
s2peak85_100

in order to calculate a ratios of each of variables 4-7 with the 
average of variables 2 and 3. I can do this directly in the long form 
by the following code:

egen step = seq(), from(0) to(5) block(1)
gen ppi2 = ((s2peak[_n-step]+s2peak[_n-step+1])/2 - 
s2peak[_n])/((s2peak[_n-step]+s2peak[_n-step+1])/2)*100
drop if s1level == 0

     +----------------------------------------------------+
     | s1level   s1s2de~y   animal   s2peak~e        ppi2 |
     |----------------------------------------------------|
  1. |      75         50   1_1_0F      472.5    46.77181 |
  2. |      75        100   1_1_0F    927.875   -4.527213 |
  3. |      85         50   1_1_0F    611.375    31.12723 |
  4. |      85        100   1_1_0F    654.375    26.28318 |
     |----------------------------------------------------|
  5. |      75         50   1_1_1F    544.875    50.87344 |
  6. |      75        100   1_1_1F    567.875    48.79973 |
  7. |      85         50   1_1_1F    443.875    59.97971 |
  8. |      85        100   1_1_1F        466     57.9849 |
     |----------------------------------------------------|
  9. |      75         50   1_1_2F    442.625   -37.08108 |
 10. |      75        100   1_1_2F        265    17.92943 |
 11. |      85         50   1_1_2F      264.5    18.08428 |
 12. |      85        100   1_1_2F    192.375    40.42141 |
     |----------------------------------------------------|
 13. |      75         50   1_1_3F    448.875    50.06605 |
 14. |      75        100   1_1_3F    462.143     48.5901 |
 15. |      85         50   1_1_3F    576.875    35.82702 |
etc.

but I'm wondering if reshape to wide and then back to long would not be 
more reliable. As long as data are not missing, I currently have no 
problems. Must I, before I go for wide, say something like,

. egen treatment = group(s1level s1s2delay), label
. drop s1level s1s2delay

     +------------------------------+
     | animal   s2peak~e   treatm~t |
     |------------------------------|
  1. | 1_1_0F     773.75       0 50 |
  2. | 1_1_0F    1001.63      0 100 |
  3. | 1_1_0F      472.5      75 50 |
  4. | 1_1_0F    927.875     75 100 |
  5. | 1_1_0F    611.375      85 50 |
  6. | 1_1_0F    654.375     85 100 |
     |------------------------------|
  7. | 1_1_1F    1116.88       0 50 |
  8. | 1_1_1F    1101.38      0 100 |
  9. | 1_1_1F    544.875      75 50 |
 10. | 1_1_1F    567.875     75 100 |
     +------------------------------+
etc.

and only then,

. reshape wide s2peakvalue, i(animal) j(treatment)

       animal  s2peak~1  s2peak~2  s2peak~3  s2peak~4  s2peak~5  
s2peak~6
  1.   1_1_0F    773.75   1001.63     472.5   927.875   611.375   
654.375
  2.   1_1_1F   1116.88   1101.38   544.875   567.875   443.875       
466
  3.   1_1_2F     309.5   336.286   442.625       265     264.5   
192.375
etc.

but then I lose my way back to the proper long format for ANOVA as well 
as the factor labels, etc.

-Dave

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