clear
set more off

************************************************
* Reference:
* A.J. Silman and G.J. Macfarlane (2002)
* Epidemiological Studies. 2nd edition
* Cambridge University Press
* pagg. 163 - 167
************************************************


************************************************
* Example 16.viii Direct age-standardisation
************************************************
input str8 city age x npyr
Hightown 1 10 9415
Hightown 2 18  8346
Hightown1 3 20 6215
Hightown1 4 22 2196
Lowtown 1 3 4103
Lowtown 2 6  3765 
Lowtown 3 12 4192
Lowtown 4 73 7426
end
label define age 1 "0-15" 2 "16-34" 3 "35-64" 4 "65+"
label values age age

* Direct standardisation
dstdize x npyr age, by(city) base("Hightown")



************************************************
* Example 16.ix Indirect age-standardisation
************************************************

* Define Hightown  as the 'standard' population
* Save it in the std_pop.dta data set
clear
input age x_stdpop npyr_stdpop
1 10 9415
2 18  8346
3 20 6215
4 22 2196
end
compress
save std_pop.dta, replace

* Input data about Lowtown
clear
input age x1 npyr1
1 3 4103
2 6  3765 
3 12 4192
4 73 7426
end
label define age 1 "0-15" 2 "16-34" 3 "35-64" 4 "65+"
label values age age

* Indirect standardisation
istdize x1 npyr1 age using std_pop, print popvars(x_stdpop npyr_stdpop)