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The data files used for the examples in this text can be downloaded in a zip file from the Wiley FTP website or the Stata Web site. You can then use a program such as WinZip to unzip the data files. If you need assistance getting data into Stata, please see our Stata Class Notes, especially the unit on Entering Data. (NOTE: The *.dat files are the data files, and the *.txt files contain the codebook information.)
use hivdata, clear
Table 1.1, page 4.
Note: The variable Censor in the book is called died in the dataset.
list
id entdate enddate time age drug died
1. 1 15may90 14oct90 5 46 0 1
2. 2 19sep89 20mar90 6 35 1 0
3. 3 21apr91 20dec91 8 30 1 1
4. 4 03jan91 04apr91 3 30 1 1
5. 5 18sep89 19jul91 22 36 0 1
6. 6 18mar91 17apr91 1 32 1 0
7. 7 11nov89 11jun90 7 36 1 1
8. 8 25nov89 25aug90 9 31 1 1
9. 9 11feb91 13may91 3 48 0 1
10. 10 11aug89 11aug90 12 47 0 1
.. [ remainder of data omitted]
Figure 1.1, page 6.
graph twoway (scatter time age if censor == 1, msymbol(X)) (scatter time age if censor == 0, msymbol(Oh)), /// ylabel(0(10)60) xlabel(15(5)55) legend(off)
Figure 1.2, page 7.
generate age2 = 1000/age graph twoway (scatter time age2 if censor == 1, msymbol(X)) (scatter time age2 if censor == 0, msymbol(Oh)), /// ylabel(0(10)60) xlabel(15(5)55) legend(off)
Table 1.2, page 14.
stset time, failure(died==0)
failure event: died == 0
obs. time interval: (0, time]
exit on or before: failure
------------------------------------------------------------------------------
100 total obs.
0 exclusions
------------------------------------------------------------------------------
100 obs. remaining, representing
80 failures in single record/single failure data
1136 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 60
streg age, dist(exp) nohr
failure _d: died == 0
analysis time _t: time
Iteration 0: log likelihood = -157.25531
Iteration 1: log likelihood = -142.27706
Iteration 2: log likelihood = -140.00561
Iteration 3: log likelihood = -140.00523
Iteration 4: log likelihood = -140.00523
Exponential regression -- log relative-hazard form
No. of subjects = 100 Number of obs = 100
No. of failures = 80
Time at risk = 1136
LR chi2(1) = 34.50
Log likelihood = -140.00523 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
age | .0939301 .0157719 5.96 0.000 .0630179 .1248424
_cons | -5.859021 .5852682 -10.01 0.000 -7.006126 -4.711917
------------------------------------------------------------------------------
Figure 1.3, page 16.
predict xb, xb
generate t = exp(-xb)
graph twoway (scatter time age if censor == 1, msymbol(X)) (scatter time age if censor == 0, msymbol(Oh)), ///
(line t age, sort), ylabel(0(10)60) xlabel(15(5)55) legend(off)
Figure 1.4, page 19.
clear input subj tp censored str11 datestr 1 1 0 "1 jan 1990" 1 2 0 "1 mar 1991" 2 1 1 "1 feb 1990" 2 2 1 "1 feb 1991" 3 1 1 "1 jun 1990" 3 2 1 "31 dec 1991" 4 1 0 "1 sep 1990" 4 2 0 "1 apr 1991" end generate date = date(datestr, "dmy") format date %dmy sort subj graph twoway (scatter subj date, connect(L) msymbol(oh)) /// (scatter subj date if censored == 0, msymbol(X))
Figure 1.5, page 20.
generate time = 0 if tp==1 replace time = (date-date[_n-1])/30.5 if tp==2 graph twoway (scatter subj time, connect(L) msymbol(oh)) /// (scatter subj time if censored == 0, msymbol(X))
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