David Airey
> Nick [Cox] helped me figure out a reshape problem where "j" in
> the reshape
> command is split amongst several variables.
>
> > I think you're moving in the right direction
> > for a -reshape- to wide. As for the ANOVA,
> > your original data structure looks better.
> >
> > egen j = concat(s1*), p("_")
> > drop s1*
> > reshape wide s2peak, i(animal) j(j) string
>
> I was going from long to wide, to calculate a ratio of experimental
> conditions, and back to wide to calculate a mixed model on
> the ratios.
> What he suggested works nicely:
>
> Here I have a sample of the data set:
>
> +----------------------------------------+
> | 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 |
> 13. | 0 50 1_1_2F 309.5 |
> 14. | 0 100 1_1_2F 336.286 |
> 15. | 75 50 1_1_2F 442.625 |
> +----------------------------------------+
>
> And I wanted to get to:
>
> animal s2peak0_50 s2peak0_100 s2peak75_50 s2peak75_100 s2peak85_50
> s2peak85_100
>
> The following code does just that and then returns to long format
> appropriate to the ANOVA.
>
> * reshape to wide
> egen j = concat(s1*), p("_")
> drop s1*
> reshape wide s2peak, i(animal) j(j) string
>
> . clist in 1/3
>
> animal s2~0_100 s2p~0_50 s~75_100 s2~75_50 s~85_100
> s2~85_50
> 1. 1_1_0F 1001.63 773.75 927.875 472.5 654.375
> 611.375
> 2. 1_1_1F 1101.38 1116.88 567.875 544.875 466
> 443.875
> 3. 1_1_2F 336.286 309.5 265 442.625
> 192.375
> 264.5
>
>
> * calculate ppi
> gen startle = (s2peakvalue0_50 + s2peakvalue0_100)/2
> gen ppi75_50 = s2peakvalue75_50 / startle * 100
> gen ppi85_50 = s2peakvalue85_50 / startle * 100
> gen ppi75_100 = s2peakvalue75_100 / startle * 100
> gen ppi85_100 = s2peakvalue85_100 / startle * 100
> drop s2* startle
>
> . clist in 1/3
>
> animal ppi75_50 ppi85_50 ppi75_100 ppi85_100
> 1. 1_1_0F 53.22819 68.87277 104.5272 73.71682
> 2. 1_1_1F 49.12656 40.02029 51.20027 42.0151
> 3. 1_1_2F 137.0811 81.91572 82.07057 59.57859
>
> *reshape to long
> reshape long ppi, i(animal) j(treatment) string
> gen str s1level_str = substr(treatment, 1, index(treatment,
> "_") - 1)
> gen str s1s2delay_str = substr(treatment, index(treatment,
> "_") + 1, .)
> encode s1level_str, generate(s1level)
> encode s1s2delay_str, generate(s1s2delay)
> drop *_str treatment
>
> . list, sep(4)
>
> +----------------------------------------+
> | animal ppi s1level s1s2de~y |
> |----------------------------------------|
> 1. | 1_1_0F 104.5272 75 100 |
> 2. | 1_1_0F 53.22819 75 50 |
> 3. | 1_1_0F 73.71682 85 100 |
> 4. | 1_1_0F 68.87277 85 50 |
> |----------------------------------------|
> 5. | 1_1_1F 51.20027 75 100 |
> 6. | 1_1_1F 49.12656 75 50 |
> 7. | 1_1_1F 42.0151 85 100 |
> 8. | 1_1_1F 40.02029 85 50 |
> |----------------------------------------|
> 9. | 1_1_2F 82.07057 75 100 |
> 10. | 1_1_2F 137.0811 75 50 |
>
> etc.
An alternative to
> gen str s1level_str = substr(treatment, 1, index(treatment,
> "_") - 1)
> gen str s1s2delay_str = substr(treatment, index(treatment,
> "_") + 1, .)
> encode s1level_str, generate(s1level)
> encode s1s2delay_str, generate(s1s2delay)
is
split treatment, p(_) destring
-split- is, broadly, speaking the inverse of -egen, concat()-.
(-split- doesn't fit within the -egen- framework, because
in general it can yield several variables.)
Nick
[email protected]
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