This lumps together all the zeros for each -id- regardless of when they
occurred.
That is valid if there is at most one spell of zeros for each -id-.
Otherwise
I don't think it matches the problem.
Nick
[email protected]
Maarten buis
bys id (observation) : gen zero = Activity == 0
bys id zero (observation) : gen nzero = _N if zero == 0
replace nzero = 0 if nzero == .
gen activity2 = activity if nzero < 60 & nzero
--- BW Wheeler <[email protected]> wrote:
I'm having trouble figuring out a solution to this data management
problem, and have exhausted all books and findit (partly as it's hard
to know what to search for)!
I have time series data captured from accelerometers, with an
observation of 'activity counts' logged every 10 seconds for several
days for each individual. If the number of counts is zero continuously
for any period of 10 minutes or more (i.e. 60+ observations), we need
to assume that the accelerometer was not being worn, and to treat
these zeros as missing.
So, my data look something like this:
Observation Date Time Activity
1 13/05/2006 15:20:00 230
2 13/05/2006 15:20:10 215
3 13/05/2006 15:20:20 0
4 13/05/2006 15:20:30 0
5 13/05/2006 15:20:40 0
...
Does anyone have any ideas of how I can replace the 'Activity' value
with missing, if that value is a zero in the midst of a continuous
series of 60+ zeros?
*
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