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Re: st: problem of stset and stsum

From   Ronán Conroy <>
Subject   Re: st: problem of stset and stsum
Date   Fri, 11 Feb 2005 10:24:51 +0000 wrote:

Dear Statalist:

May I ask for help from stata experts?

Actually, Stata gave you a lot of help - have a look!

I have a hospital data with patient ID (hrn), separation dates (sep_date) and
discharge status (dis_sta2, for those deceased coded as 1 others as 0).
The causes of admission in the data are classified as either CHD (cond=1) or
other (cond=0). The data contains at least one CHD admission for each patient.
There are 5882 subjects with 21299 admissions.

I am trying to analyse the survival of patients with CHD, using the following
statement. I came across the following problems.
1. The result shows that only 2519 subjects are left, originally there are 5882.

Stata has given you a detailed breakdown of the reasons you have lost a lot of data. You have a problem with your dates, so that a lot of participants exit at or before the time they enter, and a lot more experience an event at or before they enter.

This problem seems to relate to your endpoint time, as the remaining observations have no events. Hence your second problem - Stata cannot calculated percentiles of the survival function unless the appropriate percentage of the participants have experienced an event.

2. 'Stsum' doesn't show me the survival time at 25%, 50% and 75%.

Could anyone tell me why?

See the Stata output below which you included in your email -



. stset sep_date, id(hrn) origin(cond=1) failure (dis_sta2=1)

id: hrn
failure event: dis_sta2 == 1
obs. time interval: (sep_date[_n-1], sep_date]
exit on or before: failure
t for analysis: (time-origin)
origin: cond==1

21299 total obs.
9839 obs. end on or before enter()
2062 obs. begin on or after (first) failure
9398 obs. remaining, representing
2519 subjects
0 failures in single failure-per-subject data
2360408 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 3561

. stsum

failure _d: dis_sta2 == 1
analysis time _t: (sep_date-origin)
origin: cond==1
id: hrn

| incidence no. of |------ Survival time -----|
| time at risk rate subjects 25% 50% 75%
total | 2360408 0 2519 . . .

. qui sort hrn sep_date

. qui by hrn: gen n=_n

. qui by hrn: gen N=_N

. sum one if n==1

Variable | Obs Mean Std. Dev. Min Max
one | 5882 1.984189 1.846311 1 16

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Ronan M Conroy ( Senior Lecturer in Biostatistics Royal College of Surgeons Dublin 2, Ireland +353 1 402 2431 (fax 2764) -------------------- Just say no to drug reps

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