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 zip 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
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