To analyse MTUS data at the person level, you need to use this combination of the identifier variables to uniquely identify people who participated in a time use survey included in MTUS:
country survey swave msamp hldid persid
Here is some example code in SPSS that allows you to compare pet care by sex by country on any given day at the person level. This code assumes that you are starting from the Aggregate file.
*main27 is time in pet care; main47 is time walking dogs.
*change not recorded in the survey -9 values to 0 for calculation simplicity.
recode main27 main47 (-9=0).
execute.
*sum total pet care time: time providing pet care + time walking dogs.
compute tpet=main27 + main47.
*make a person level file - this file will have the identifiers, your new total pet care time, the number of diary days association with this person, sex and age.
aggregate
outfile=*
/break country survey swave msamp hldid persid
/tpetcare=SUM(tpet)
/ndays=n /sex=max(sex) /age=max(age).
compute dpetcare=tpetcare/ndays.
var lab dpetcare average time on any given day looking after a pet.
var lab ndays number of diary days this person completed.
means dpetcare by sex by countrya.
*this last step looks only at people who reported any time in pet care in any one of their diaries.
temp.
select if sex>-8 and dpetcare>0.
means dpetcare by sex by countrya.
*note that this approach takes an average across all diary days completed by each person. As some surveys collect only one diary while other surveys collect more than one diary, users will need to think about how the differences in the number of diaries collected in each survey that they analyse affect their results.