Hi all,

I have a dataset looking as follows:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input int year float id_indication str83 IndicationName float(treated launch_year_first_cell) double prod_ann_sales
2015 1 "Abdominal aortic aneurysm"                0 .                  0
2016 1 "Abdominal aortic aneurysm"                0 .                  0
2017 1 "Abdominal aortic aneurysm"                0 .                  0
2018 1 "Abdominal aortic aneurysm"                0 .                  0
2019 1 "Abdominal aortic aneurysm"                0 .                  0
2020 1 "Abdominal aortic aneurysm"                0 .                  0
2021 1 "Abdominal aortic aneurysm"                0 .                  0
2022 1 "Abdominal aortic aneurysm"                0 .                  0
2023 1 "Abdominal aortic aneurysm"                0 .   21.8633333333333
2024 1 "Abdominal aortic aneurysm"                0 .   53.7966666666667
2025 1 "Abdominal aortic aneurysm"                0 .              84.28
2026 1 "Abdominal aortic aneurysm"                0 .   113.393333333333
2015 2 "Achondroplasia"                           2016   1163.23574203499
2016 2 "Achondroplasia"                           2016    1303.2157934352
2017 2 "Achondroplasia"                           2016   1011.17575275825
2018 2 "Achondroplasia"                           2016     1083.2157251451
2019 2 "Achondroplasia"                           2016   1090.82350163661
2020 2 "Achondroplasia"                           2016   1179.97440868719
2021 2 "Achondroplasia"                           2016 1223.9224860606562
2022 2 "Achondroplasia"                           2016 1293.0416237264178
2023 2 "Achondroplasia"                           2016 1420.8981733000492
2024 2 "Achondroplasia"                           2016 1589.9391177204116
2025 2 "Achondroplasia"                           2016  1852.242825747795
2026 2 "Achondroplasia"                           2016  2098.367633202445
2015 3 "Acid-related dyspepsia"                   0 .  385.5409559772426
2016 3 "Acid-related dyspepsia"                   0 .  355.6929774027395
2017 3 "Acid-related dyspepsia"                   0 . 381.41060827522364
2018 3 "Acid-related dyspepsia"                   0 .   386.799461705437
2019 3 "Acid-related dyspepsia"                   0 .   300.476492474147
2020 3 "Acid-related dyspepsia"                   0 . 202.49361787399036
2021 3 "Acid-related dyspepsia"                   0 . 228.90110325097507
2022 3 "Acid-related dyspepsia"                   0 . 226.16186369057772
2023 3 "Acid-related dyspepsia"                   0 . 222.00651822704063
2024 3 "Acid-related dyspepsia"                   0 . 217.66185051459985
2025 3 "Acid-related dyspepsia"                   0 .   214.727676749817
2026 3 "Acid-related dyspepsia"                   0 . 212.26663479235557
2015 4 "Acne"                                     0 .  2258.063099020268
2016 4 "Acne"                                     0 . 1966.7606963581804
2017 4 "Acne"                                     0 .  1801.770638404245
2018 4 "Acne"                                     0 . 1678.2880184673706
2019 4 "Acne"                                     0 . 1575.2476318817926
2020 4 "Acne"                                     0 . 1570.7339948396063
2021 4 "Acne"                                     0 . 1646.9662555222505
2022 4 "Acne"                                     0 . 1732.2217298349751
2023 4 "Acne"                                     0 . 1866.0471322873602
2024 4 "Acne"                                     0 . 1987.9143855539958
2025 4 "Acne"                                     0 . 2083.4991115826656
2026 4 "Acne"                                     0 .  2206.484618818403
2015 5 "Acromegaly"                               0 . 1998.6214246220125
2016 5 "Acromegaly"                               0 . 2072.6613134891177
2017 5 "Acromegaly"                               0 . 2069.2273626703222
2018 5 "Acromegaly"                               0 . 2019.5289616017235
2019 5 "Acromegaly"                               0 . 2041.3132067482168
2020 5 "Acromegaly"                               0 .  2014.163795738852
2021 5 "Acromegaly"                               0 . 1951.3060433715675
2022 5 "Acromegaly"                               0 . 1794.5447511705975
2023 5 "Acromegaly"                               0 . 1609.8826430457325
2024 5 "Acromegaly"                               0 . 1500.0167300613577
2025 5 "Acromegaly"                               0 .  1461.306107095164
2026 5 "Acromegaly"                               0 . 1444.0853372727947
2015 6 "Actinic keratosis"                        0 .  375.3044829091662
2016 6 "Actinic keratosis"                        0 . 197.96140632044785
2017 6 "Actinic keratosis"                        0 .  213.5143751056571
2018 6 "Actinic keratosis"                        0 .  267.6492265368961
2019 6 "Actinic keratosis"                        0 . 180.28720943686253
2020 6 "Actinic keratosis"                        0 .  78.45472173605228
2021 6 "Actinic keratosis"                        0 .   93.9275036119191
2022 6 "Actinic keratosis"                        0 . 113.62612510585552
2023 6 "Actinic keratosis"                        0 .  145.7289865973963
2024 6 "Actinic keratosis"                        0 . 179.10831358747976
2025 6 "Actinic keratosis"                        0 . 208.14323503324482
2026 6 "Actinic keratosis"                        0 . 241.98066014984138
2015 7 "Acute Radiation Syndrome"                 2011               1049
2016 7 "Acute Radiation Syndrome"                 2011                765
2017 7 "Acute Radiation Syndrome"                 2011                549
2018 7 "Acute Radiation Syndrome"                 2011                365
2019 7 "Acute Radiation Syndrome"                 2011                264
2020 7 "Acute Radiation Syndrome"                 2011                225
2021 7 "Acute Radiation Syndrome"                 2011   133.062166233333
2022 7 "Acute Radiation Syndrome"                 2011   107.064829816667
2023 7 "Acute Radiation Syndrome"                 2011   95.3222947833333
2024 7 "Acute Radiation Syndrome"                 2011   86.0040361884058
2025 7 "Acute Radiation Syndrome"                 2011   75.1362600124134
2026 7 "Acute Radiation Syndrome"                 2011   66.6616121581944
2015 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2016 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2017 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2018 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2019 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2020 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2021 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2022 8 "Acute decompensated heart failure (ADHF)" 0 .                  0
2023 8 "Acute decompensated heart failure (ADHF)" 0 .               1.25
2024 8 "Acute decompensated heart failure (ADHF)" 0 .                  4
2025 8 "Acute decompensated heart failure (ADHF)" 0 .                8.5
2026 8 "Acute decompensated heart failure (ADHF)" 0 .                 13
2015 9 "Acute kidney injury"                      0 .                  0
2016 9 "Acute kidney injury"                      0 .                  0
2017 9 "Acute kidney injury"                      0 .                  0
2018 9 "Acute kidney injury"                      0 .                  0
end
basically this is a balanced panel of indications sales observed (or predicted) from 2015 to 2026. Some of the indications have been treated but the time period of the treatment differs from indication to indication (in the dataex, one has treatment beginning from 2016 and the other from 2011). What I would like to do is:
1) make a diff in diff that is suited for balanced panel with different treatment periods;
2) make pre-post plot where I have an xline on the normalized treatment period, treated and control units (i.e. a normal plot of diff in diff with normalized years instead, say 0 = treatment period, negative periods are periods before treatment and positive periods are periods after treatment).

Is it possible to do soo in Stata 13?

Thank you,

Federico