|
|
|
||||
|
|
|||||
Table 7.1 on page 211.
use http://www.ats.ucla.edu/stat/examples/asa2/actg320, clear
stset time, fail(censor)
failure event: censor != 0 & censor < .
obs. time interval: (0, time]
exit on or before: failure
------------------------------------------------------------------------------
1151 total obs.
0 exclusions
------------------------------------------------------------------------------
1151 obs. remaining, representing
96 failures in single record/single failure data
264941 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 364
generate ivdrug_d=ivdrug>1
generate karnof_90=(karnof==90)
generate karnof_70_80=(karnof==70|karnof==80)
centile cd4, c(25 50 75)
-- Binom. Interp. --
Variable | Obs Percentile Centile [95% Conf. Interval]
-------------+-------------------------------------------------------------
cd4 | 1151 25 23 19.5 26.09482
| 50 74.5 67.5 80.5
| 75 136.5 130 141.1559
generate cd4_q=1
replace cd4_q=2 if cd4>23 & cd4<=74.5
replace cd4_q=3 if cd4>74.5 & cd4<=136.5
replace cd4_q=4 if cd4>136.5
stcox tx ivdrug_d karnof_70_80 karnof_90 age, nolog nohr strata(cd4_q) ///
bases(s0)
failure _d: censor
analysis time _t: time
Stratified Cox regr. -- Breslow method for ties
No. of subjects = 1151 Number of obs = 1151
No. of failures = 96
Time at risk = 264941
LR chi2(5) = 36.73
Log likelihood = -506.75521 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
tx | -.6677746 .215533 -3.10 0.002 -1.090212 -.2453376
ivdrug_d | -.5463155 .3225604 -1.69 0.090 -1.178522 .0858912
karnof_70_80 | 1.191 .2962962 4.02 0.000 .6102697 1.77173
karnof_90 | .4118837 .2926676 1.41 0.159 -.1617343 .9855017
age | .0224756 .0112014 2.01 0.045 .0005213 .04443
------------------------------------------------------------------------------
Stratified by cd4_q
Figure 7.1 on page 212 using the model from previous example.
local tx=_b[tx] predict r,xb replace r = r-tx*_b[tx] table cd4_q, con(median r)
----------------------
cd4_q | med(r)
----------+-----------
1 | 1.217556
2 | 1.176055
3 | 1.086152
4 | 1.093729
----------------------
sort time
foreach i of numlist 1/4 {
quietly sum r if cd4_q==`i', detail
local median = r(p50)
gen s`i' = s0^(exp(`median'))
gen s`i'_tr = s0^(exp(`median'+`tx'))
scatter s`i' s`i'_tr time if cd4_q==`i', sort ms(none none) c(J J) clpattern(dash solid) ///
ylabel(0.8(0.05)1) title( "CD4 Quartile `i'" , size(medsmall) pos(12) ) ///
ytitle(Adjusted Survival Function) ylabel(,nogrid angle(horizontal)) ///
xtitle("Time") legend(off) name(s`i', replace)
}
Table 7.2 on page 217 and Table 7.3 on page 219 using uis data.
use http://www.ats.ucla.edu/stat/examples/asa2/uis, clear
generate enter=410-los
generate exit=410+(time-los)
stset exit, enter(enter) fail(censor) id(id)
id: id
failure event: censor != 0 & censor < .
obs. time interval: (exit[_n-1], exit]
enter on or after: time enter
exit on or before: failure
------------------------------------------------------------------------------
628 total obs.
0 exclusions
------------------------------------------------------------------------------
628 obs. remaining, representing
628 subjects
508 failures in single failure-per-subject data
147394 total analysis time at risk, at risk from t = 0
earliest observed entry t = 10
last observed exit t = 1531
stsplit off_tx, at(0,410)
replace off_tx=1 if off_tx==410
rename _t oldt
stset oldt, origin(_t0) id(id) fail(censor)
id: id
failure event: censor != 0 & censor < .
obs. time interval: (oldt[_n-1], oldt]
exit on or before: failure
t for analysis: (time-origin)
origin: time oldt0
------------------------------------------------------------------------------
1174 total obs.
0 exclusions
------------------------------------------------------------------------------
1174 obs. remaining, representing
628 subjects
508 failures in single failure-per-subject data
147394 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 1172
xi:stcox i.treat*off_tx, nolog nohr
i.treat _Itreat_0-1 (naturally coded; _Itreat_0 omitted)
i.treat*off_tx _ItreXoff_t_# (coded as above)
failure _d: censor
analysis time _t: (oldt-origin)
origin: time oldt0
id: id
Cox regression -- Breslow method for ties
No. of subjects = 628 Number of obs = 1174
No. of failures = 508
Time at risk = 147394
LR chi2(3) = 387.12
Log likelihood = -2766.9447 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Itreat_1 | -.52389 .2258328 -2.32 0.020 -.9665141 -.081266
off_tx | 2.270329 .1865035 12.17 0.000 1.904789 2.635869
_ItreXoff_~1 | .6209768 .2463036 2.52 0.012 .1382306 1.103723
------------------------------------------------------------------------------
Table 7.3
xi:stcox i.treat*off_tx, nolog
i.treat _Itreat_0-1 (naturally coded; _Itreat_0 omitted)
i.treat*off_tx _ItreXoff_t_# (coded as above)
failure _d: censor
analysis time _t: (oldt-origin)
origin: time oldt0
id: id
Cox regression -- Breslow method for ties
No. of subjects = 628 Number of obs = 1174
No. of failures = 508
Time at risk = 147394
LR chi2(3) = 387.12
Log likelihood = -2766.9447 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
_t | Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Itreat_1 | .5922123 .1337409 -2.32 0.020 .3804068 .9219485
off_tx | 9.682585 1.805836 12.17 0.000 6.717989 13.95544
_ItreXoff_~1 | 1.860745 .4583082 2.52 0.012 1.14824 3.015372
------------------------------------------------------------------------------
lincom _Itreat_1 + _ItreXoff_t_1
( 1) _Itreat_1 + _ItreXoff_t_1 = 0
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .0970868 .097709 0.99 0.320 -.0944193 .2885929
------------------------------------------------------------------------------
di exp( r(estimate) )
1.101956
di exp( r(estimate) + 1.96*r(se))
1.334553
di exp( r(estimate) - 1.96*r(se))
.90989798
lincom off_tx + _ItreXoff_t_1
( 1) off_tx + _ItreXoff_t_1 = 0
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 2.891306 .2050128 14.10 0.000 2.489488 3.293123
------------------------------------------------------------------------------
di exp( r(estimate) )
18.01682
di exp( r(estimate) + 1.96*r(se))
26.927036
di exp( r(estimate) - 1.96*r(se))
12.055015
Table 7.5 on page 222 and Table 7.6 on page 223 using grace1000 data.
use http://www.ats.ucla.edu/stat/examples/asa2/grace1000, clear
stset days, fail(death)
failure event: death != 0 & death < .
obs. time interval: (0, days]
exit on or before: failure
------------------------------------------------------------------------------
1000 total obs.
0 exclusions
------------------------------------------------------------------------------
1000 obs. remaining, representing
324 failures in single record/single failure data
109847.5 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 180
generate age_inv = 1/age*1000
generate sysbp_sqrt = sqrt(sysbp)
stcox revasc age_inv sysbp_sqrt st , nolog nohr
failure _d: death
analysis time _t: days
Cox regression -- Breslow method for ties
No. of subjects = 1000 Number of obs = 1000
No. of failures = 324
Time at risk = 109847.5
LR chi2(4) = 185.82
Log likelihood = -2043.7251 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
revasc | -.5296277 .1171956 -4.52 0.000 -.759327 -.2999285
age_inv | -.1890701 .0224795 -8.41 0.000 -.2331292 -.145011
sysbp_sqrt | -.2072934 .0386913 -5.36 0.000 -.2831269 -.1314599
stchange | .5134163 .1188503 4.32 0.000 .2804741 .7463586
------------------------------------------------------------------------------
Table 7.6
generate enter=200-revascdays
generate exit=200+(days-revascdays)
stset exit, enter(enter) fail(death) id(id)
id: id
failure event: death != 0 & death < .
obs. time interval: (exit[_n-1], exit]
enter on or after: time enter
exit on or before: failure
------------------------------------------------------------------------------
1000 total obs.
0 exclusions
------------------------------------------------------------------------------
1000 obs. remaining, representing
1000 subjects
324 failures in single failure-per-subject data
109847.5 total analysis time at risk, at risk from t = 0
earliest observed entry t = 20
last observed exit t = 380
stsplit revasc_t, at(0,200)
replace revasc_t=1 if revasc_t==200
replace revasc_t=0 if revasc==0
stset _t, origin(_t0) id(id) fail(death)
id: id
failure event: death != 0 & death < .
obs. time interval: (_t[_n-1], _t]
exit on or before: failure
t for analysis: (time-origin)
origin: time _t0
------------------------------------------------------------------------------
1359 total obs.
0 exclusions
------------------------------------------------------------------------------
1359 obs. remaining, representing
1000 subjects
324 failures in single failure-per-subject data
109847.5 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 180
stcox revasc_t age_inv sysbp_sqrt st , nolog nohr
failure _d: death
analysis time _t: (_t-origin)
origin: time _t0
id: id
Cox regression -- Breslow method for ties
No. of subjects = 1000 Number of obs = 1359
No. of failures = 324
Time at risk = 109847.5
LR chi2(4) = 169.38
Log likelihood = -2051.946 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
revasc_t | -.2609491 .1237083 -2.11 0.035 -.503413 -.0184853
age_inv | -.2020569 .0228396 -8.85 0.000 -.2468218 -.1572921
sysbp_sqrt | -.2146887 .0391799 -5.48 0.000 -.2914798 -.1378975
stchange | .500509 .1190631 4.20 0.000 .2671496 .7338684
------------------------------------------------------------------------------
UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services