I have a dataset of this type:
+---------------------------------------------------------------------------------------------------+
idnum wt20 wt30 wt40 wt50 wt60 wt70
weight age_ref weightlst
---------------------------------------------------------------------------------------------------
708 61.23497 61.23497 63.50293 61.23497 86.18255 . 90
60 60
713 56.69905 79.37866 81.64663 104.3262 . . 100
58 50
721 102.0583 147.4175 . . . . 180.54
39 30
+---------------------------------------------------------------------------------------------------+
where:
wt*: weight captured at different ages (10-yr interval)
weight: weight at reference time
age_ref: age at reference time
weightlst: age at last measurement before reference
I am trying to create a measure of weight fluctuation as follows:
-----------------------------
gen delta1 = abs(wt20 - wt30)
gen delta2 = abs(wt30 - wt40)
gen delta3 = abs(wt40 - wt50)
gen delta4 = abs(wt50 - wt60)
gen delta5 = abs(wt60 - wt70)
egen weight_decades = rowtotal(delta1 delta2 delta3 delta4 delta5)
-----------------------------
I would like to also capture the last interval for some people. For
example for id==721, I have weight measured at reference (age 39) but the
last recorded weight is at age 30 (wt30). Thus, the above code will only
compute 1 interval.
In general, if age_ref > weightlst, I need one more interval computed .
The preferred way would be to automate my code above to include these
instances. Thanks for any help.
Thomas Speidel
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