I don't completely follow this, but if you want the predicted values for
each pt_id you can use -levelsof- and -foreach- to loop through the groups.
Note: you have repeated time values for pt_id =2, 01 Aug 06.
Perhaps this will help:
clear
input pt_id str9 appt_date str9 appt_status bp_systolic
1 "21 Apr 05" "No Show" .
1 "07 Jun 05" "Completed" 140
1 "11 Jan 06" "Completed" 150
1 "16 Feb 06" "Completed" 150
1 "30 Mar 06" "Canceled" .
1 "02 May 06" "Canceled" .
1 "09 May 06" "Completed" 138
1 "11 Jul 06" "Completed" 142
1 "19 Sep 06" "Completed" 150
2 "30 May 06" "No Show" .
2 "11 Jul 06" "Completed" 176
2 "25 Jul 06" "Completed" 121
2 "01 Aug 06" "Canceled" .
2 "01 Aug 06" "Completed" 101
2 "15 Aug 06" "Completed" 118
2 "22 Aug 06" "Canceled" .
2 "12 Sep 06" "Completed" 136
2 "14 Nov 06" "Completed" 137
2 "16 Jan 07" "Completed" 113
2 "06 Feb 07" "No Show" .
2 "03 May 06" "Canceled" .
2 "25 Jul 06" "Canceled" .
2 "01 Aug 06" "Canceled" .
2 "07 Feb 07" "Canceled" .
end
gen date = date(appt_d, "dm20y")
format date %d
sort pt date appt_s
by pt (date): drop if date == date[_n+1]
tsset pt date
qui {
gen expect_bp = .
levelsof pt, local(levels)
foreach l of local levels {
reg bp date if pt == `l'
predict foo if pt == `l', xb
replace expect = foo if pt == `l'
drop foo
}
}
mark tag if expect>140
l, sepby(pt) ab(20)
Scott
> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Andrew O'Connor DO
> Sent: Wednesday, April 25, 2007 7:32 AM
> To: [email protected]
> Subject: st: Using Stata to calculate proportion of observation time above
> a threshold value i.e. "time in range"
>
> I'm hoping someone can help me with a data problem (Nik sorry I emailed
> you directly rather than putting on the list).
>
> A person I work with was able to calculate this in SAS and I'm hopefully
> able to do the same in STATA. I'm trying to use stata to calculate a
> time in range for blood pressure data
> here is what my data looks like
> ------------------------------
> -----------------------------------------------------------------
> Pt_ID Appt_date appt_status bp_systolic
> 1 21 Apr 05 No Show
> 1 07 Jun 05 Completed 140
> 1 11 Jan 06 Completed 150
> 1 16 Feb 06 Completed 150
> 1 30 Mar 06 Canceled
> 1 02 May 06 Canceled
> 1 09 May 06 Completed 138
> 1 11 Jul 06 Completed 142
> 1 19 Sep 06 Completed 150
> 2 30 May 06 No Show
> 2 11 Jul 06 Completed 176
> 2 25 Jul 06 Completed 121
> 2 01 Aug 06 Canceled
> 2 01 Aug 06 Completed 101
> 2 15 Aug 06 Completed 118
> 2 22 Aug 06 Canceled
> 2 12 Sep 06 Completed 136
> 2 14 Nov 06 Completed 137
> 2 16 Jan 07 Completed 113
> 2 06 Feb 07 No Show
> 2 03 May 06 Canceled
> 2 25 Jul 06 Canceled
> 2 01 Aug 06 Canceled
> 2 07 Feb 07 Canceled
> --------------------------------------------------------------------------
> -----------------------------
> Basically I assume a linear slope (interpolated) between successive
> dates, set a threshold, then ask STATA to calculate the proportion of
> total observation time that the curve was above my threshold.
>
> I think this falls under the cross sectional time series definition.
> Basically what I'm trying to do is each individual (where iis Pt_ID) has
> a unique observation time (tis Appt_date) and a set of observed systolic
> blood pressures (bp_systolic). There are no set observation times, this
> is observational data. For each time, I assume a linear slope of blood
> pressure change to the next observation time. I need to calculate the
> area that the slope measure predicts blood pressure over my threshold
> (say 140 for example). Slopes can be positive or negative or flat.
> Each individual has a variable number of observations, they are not
> equally spaced, and missing data is a possibility.
>
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