standardize BMI over age group and then run quantile regression

[Raphael George]

How do I standardize the BMI over age groups to create a BMI z score and then run a quantile regression?

This is the code i used for non-standardized BMI

foreach c in 10 25 50 75 90{
    bootstrap, reps(999) : rifhdreg BMI treated  , rif(q(`i')) abs(HHPBASE SURVEY COTOTAL5 EW9  district_id#c.SURVEY) cluster(IDPSU)
    eststo q`i'
    }

Listed 100 out of 19421 observations
Use the count() option to list more

. dataex BMI treated age

----------------------- copy starting from the next line -----------------------

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(BMI treated) int age
 23.17475 0 40
29.602175 0 33
 25.46452 0 26
 23.49591 0 33
 24.63776 1 47
 20.61365 1 42
16.829824 1 39
 23.42016 1 56
 16.97294 0 28
 20.89844 0 35
  30.0864 0 29
 31.99797 1 36
28.358147 0 35
 23.85799 0 42
 21.52873 1 35
25.561056 1 42
 21.99219 1 47
 22.47699 0 40
 19.98344 0 29
21.733334 0 22
 25.13861 1 39
 29.13409 1 53
20.148024 1 34
18.203485 0 27
 21.77648 1 40
25.764605 0 33
 29.29406 1 49
10.683762 1 34
26.414253 1 55
14.327621 1 48
  23.6671 0 35
19.058865 0 28
21.426653 1 49
 23.21406 1 52
  25.7553 0 39
22.221287 0 25
26.074083 1 54
16.210938 1 42
 19.51093 0 28
 21.75343 0 21
22.852877 1 47
27.140844 1 46
 24.06643 0 39
 25.60617 1 45
 23.15688 0 25
23.684183 0 30
21.395906 1 42
22.192595 1 47
15.231208 1 52
23.702597 1 43
 21.55471 0 29
 18.02873 1 35
19.060251 1 52
 28.56713 0 43
 29.56929 0 49
 31.92075 0 33
 29.38885 0 27
19.285105 1 52
20.625706 0 36
22.902575 0 29
17.975086 1 45
18.076817 0 36
 22.96625 0 43
 26.92532 1 50
25.838005 1 39
 27.09817 1 51
  21.5625 0 30
 24.66638 0 34
 21.91004 1 47
19.214306 1 52
   26.074 1 47
21.515976 1 35
 30.93434 1 45
 31.52137 1 43
 26.20687 1 50
 21.11217 1 45
 26.71052 0 37
25.190445 0 30
17.962257 0 26
24.156216 0 33
24.969816 1 45
24.221455 1 49
 17.07068 1 55
  21.5888 0 42
35.761723 1 49
 25.01561 0 35
24.667496 0 42
18.897823 1 42
19.063108 1 45
 28.56986 1 55
 21.82271 1 50
  23.4566 1 43
23.680254 1 42
 23.51915 1 42
 24.60118 1 35
 39.59719 1 47
 24.21429 1 42
28.983206 1 47
 34.25031 1 45
27.985754 1 50
end

------------------ copy up to and including the previous line ------------------

Listed 100 out of 19421 observations
Use the count() option to list more

[Daniel Schaefer]

How do I standardize the BMI over age groups to create a BMI z score

Its not clear what you mean by age groups, but if you mean "group by age" then:

bysort age: egen std_bmi = std(BMI)