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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