UCLA Academic Technology Services HomeServicesClassesContactJobs
Search

Stata Textbook Examples
Applied Survival Analysis by Hosmer and Lemeshow
Chapter 3: Regression Models for Survival Data

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.)
Table 3.1, page 98.
use hmohiv, clear

stset time, failure(censor)
stcox age, nohr

Cox regression -- Breslow method for ties

No. of subjects =          100                     Number of obs   =       100
No. of failures =           80
Time at risk    =         1136
                                                   LR chi2(1)      =     21.35
Log likelihood  =   -288.51804                     Prob > chi2     =    0.0000

------------------------------------------------------------------------------
          _t |
          _d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .0814042   .0174352     4.67   0.000     .0472317    .1155766
------------------------------------------------------------------------------
Table 3.2, page 103.
generate ad = age*drug
stcox age drug ad, nohr
lrtest, saving(0)

Cox regression -- Breslow method for ties

No. of subjects =          100                     Number of obs   =       100
No. of failures =           80
Time at risk    =         1136
                                                   LR chi2(3)      =     35.02
Log likelihood  =   -281.68438                     Prob > chi2     =    0.0000

------------------------------------------------------------------------------
          _t |
          _d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .0942309   .0229261     4.11   0.000     .0492965    .1391653
        drug |   1.185909   1.256515     0.94   0.345    -1.276816    3.648634
          ad |  -.0067029   .0337407    -0.20   0.843    -.0728334    .0594276
------------------------------------------------------------------------------
Table 3.3, page 105.
stcox age drug, nohr

Cox regression -- Breslow method for ties

No. of subjects =          100                     Number of obs   =       100
No. of failures =           80
Time at risk    =         1136
                                                   LR chi2(2)      =     34.98
Log likelihood  =   -281.70404                     Prob > chi2     =    0.0000

------------------------------------------------------------------------------
          _t |
          _d | Haz. Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   1.095852     .02026     4.95   0.000     1.056854    1.136289
        drug |   2.563531   .6550089     3.68   0.000      1.55363    4.229893
------------------------------------------------------------------------------
Compute G, page 105.
lrtest

Cox:  likelihood-ratio test                           chi2(1)     =       0.04
                                                      Prob > chi2 =     0.8428
Table 3.4, page 108.
stcox age drug, nohr

Cox regression -- Breslow method for ties

No. of subjects =          100                     Number of obs   =       100
No. of failures =           80
Time at risk    =         1136
                                                   LR chi2(2)      =     34.98
Log likelihood  =   -281.70404                     Prob > chi2     =    0.0000

------------------------------------------------------------------------------
          _t |
          _d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .0915319   .0184879     4.95   0.000     .0552963    .1277675
        drug |   .9413856   .2555104     3.68   0.000     .4405943    1.442177
------------------------------------------------------------------------------

stcox age drug, exactm nohr

Cox regression -- exact marginal likelihood

No. of subjects =          100                     Number of obs   =       100
No. of failures =           80
Time at risk    =         1136
                                                   LR chi2(2)      =     39.27
Log likelihood  =   -199.57935                     Prob > chi2     =    0.0000

------------------------------------------------------------------------------
          _t |
          _d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |    .097677    .018738     5.21   0.000     .0609512    .1344027
        drug |   1.022633   .2571643     3.98   0.000     .5186006    1.526666
------------------------------------------------------------------------------

stcox age drug, efron nohr

Cox regression -- Efron method for ties

No. of subjects =          100                     Number of obs   =       100
No. of failures =           80
Time at risk    =         1136
                                                   LR chi2(2)      =     39.13
Log likelihood  =   -276.35726                     Prob > chi2     =    0.0000

------------------------------------------------------------------------------
          _t |
          _d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .0971408   .0186397     5.21   0.000     .0606077     .133674
        drug |   1.016698    .256217     3.97   0.000     .5145222    1.518875
------------------------------------------------------------------------------

How to cite this page

Report an error on this page

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


The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California