# Re: st: comparing -ltable- and -sts list-

 From Philip Ryan To statalist@hsphsun2.harvard.edu Subject Re: st: comparing -ltable- and -sts list- Date Mon, 03 Nov 2008 14:01:01 +1030

```Michael

```
I think that to perform a test *at a particular time*, as opposed to an overall (logrank style) test, using the K-M estimator you need to
```
```
(i) estimate the S(t) and the Greenwood variance for each group at the chosen time
```(ii) perform a z test

Step (i) can be done by sts list:

. sts list , by(drug) at(0,2)

failure _d:  died
analysis time _t:  studytime

Beg.                      Survivor      Std.
```
Time Total Fail Function Error [95% Conf. Int.]
```-------------------------------------------------------------------------------
drug=1
0         0        0              1.0000         .          .         .
2        18        3              0.8500    0.0798     0.6038    0.9490
drug=2
0         0        0              1.0000         .          .         .
2         0        0              1.0000         .          .         .
drug=3
0         0        0              1.0000         .          .         .
2         0        0              1.0000         .          .         .
-------------------------------------------------------------------------------

```
Note the syntax of the -at()- option. Had I just put -at(2)- Stata would have given me its 2 chosen times, not necessarily t=2. (Try it and see!)
```
```
Then you can retrieve S(t=2) for each of the two groups of interest and the SEs and thus calculate the Greenwood estimate of the variance of the difference in S(t). The z test follows...
```
Step (ii):

z = (S1(t=2) - S2(t=2)) /  [  sqrt(Var(S1(t=2) + Var(S2(t=2))]

```
where Var(S(t=2) is the square of the SE for the respective group at the desired time.
```
whence you can use the -normal()- function to get your P value.

```
Doesn't look like your particular data (at t=2) will support this test - we only get an estimate for drug=1. But the above is the general idea. Someone else may know of a more direct way.
```
Phil

At 11:33 AM 3/11/2008, you wrote:
```
```Thanks Phil.

```
Is there a way to use -sts list- to statistically compare the 2-year survival rates between two groups? I notice that the -compare- option simply places them next to each other without a statistical test.
```
Michael

```
```Michael

use the   -noadjust-   option  on  -ltable-

from -help ltable- :

```
noadjust suppresses the actuarial adjustment for deaths and censored observations. The default is to consider the adjusted number at risk at the start of the interval to be total at the start minus (the number dead or censored)/2. If noadjust is specified, the number at risk is simply the total at the start, corresponding to the standard Kaplan-Meier assumption. noadjust should be specified when using ltable to list results corresponding to those
```        produced by sts list.

Phil

At 09:51 AM 3/11/2008, you wrote:
```
```Dear Statalist members,
```
I had the impression that both -ltable- and -sts list- would list the survivor function per failure period. However, they give slightly different answers. In the example below, for drug3 -ltable- shows survival at 24 months as 77.14%, whereas -sts list- says it's 64.29%
```
sysuse cancer.dta, clear
sts list, by(drug)
ltable _t died, by(drug)

Could anyone help me to clarify this?

--

Best wishes,
Michael McCulloch

Pine Street Foundation
124 Pine St., San Anselmo, CA 94960-2674
Tel:    (415) 407-1357
Fax:    (415) 485-1065
mcculloch@pinestreetfoundation.org
www.pinestreetfoundation.org
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```
```
Philip Ryan
Professor,
Discipline of Public Health

Director, Data Management & Analysis Centre

Associate Dean (IT)
Faculty of Health Sciences

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```
Philip Ryan
Professor,
Discipline of Public Health

Director, Data Management & Analysis Centre

Associate Dean (IT)
Faculty of Health Sciences

Discipline of Public Health
Mail Drop DX650 511
South Australia

location:
Level 6, Room 6-18
Bice Building
North Terrace

tel +61 8 8303 3570
fax +61 8 8223 4075
CRICOS Provider Number 00123M
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notify the sender by reply email and immediately delete
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```