### Stata Textbook Examples Applied Logistic Regression, Second Edition, by Hosmer and Lemeshow Chapter 1: Introduction to the Logistic Regression Model

The data files used for the examples in this text can be downloaded in a .zip file from the Wiley Publications website.  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 1.1, page 3.
use chdage.dta, clear
(Hosmer and Lemeshow - from chapter 1)

gen agrp=age
recode agrp 20/29=1 30/34=2 35/39=3 40/44=4 45/49=5 50/54=6 55/59=7 60/69=8
(100 changes made)

list id age agrp chd

id        age       agrp        chd
1.         1         20          1          0
2.         2         23          1          0
3.         3         24          1          0
4.         4         25          1          0
5.         5         25          1          1
6.         6         26          1          0
7.         7         26          1          0
8.         8         28          1          0
9.         9         28          1          0
10.        10         29          1          0
11.        11         30          2          0
12.        12         30          2          0
13.        13         30          2          0
14.        14         30          2          0
15.        15         30          2          0
16.        16         30          2          1
17.        17         32          2          0
18.        18         32          2          0
19.        19         33          2          0
20.        20         33          2          0
21.        21         34          2          0
22.        22         34          2          0
23.        23         34          2          1
24.        24         34          2          0
25.        25         34          2          0
26.        26         35          3          0
27.        27         35          3          0
28.        28         36          3          0
29.        29         36          3          1
30.        30         36          3          0
31.        31         37          3          0
32.        32         37          3          1
33.        33         37          3          0
34.        34         38          3          0
35.        35         38          3          0
36.        36         39          3          0
37.        37         39          3          1
38.        38         40          4          0
39.        39         40          4          1
40.        40         41          4          0
41.        41         41          4          0
42.        42         42          4          0
43.        43         42          4          0
44.        44         42          4          0
45.        45         42          4          1
46.        46         43          4          0
47.        47         43          4          0
48.        48         43          4          1
49.        49         44          4          0
50.        50         44          4          0
51.        51         44          4          1
52.        52         44          4          1
53.        53         45          5          0
54.        54         45          5          1
55.        55         46          5          0
56.        56         46          5          1
57.        57         47          5          0
58.        58         47          5          0
59.        59         47          5          1
60.        60         48          5          0
61.        61         48          5          1
62.        62         48          5          1
63.        63         49          5          0
64.        64         49          5          0
65.        65         49          5          1
66.        66         50          6          0
67.        67         50          6          1
68.        68         51          6          0
69.        69         52          6          0
70.        70         52          6          1
71.        71         53          6          1
72.        72         53          6          1
73.        73         54          6          1
74.        74         55          7          0
75.        75         55          7          1
76.        76         55          7          1
77.        77         56          7          1
78.        78         56          7          1
79.        79         56          7          1
80.        80         57          7          0
81.        81         57          7          0
82.        82         57          7          1
83.        83         57          7          1
84.        84         57          7          1
85.        85         57          7          1
86.        86         58          7          0
87.        87         58          7          1
88.        88         58          7          1
89.        89         59          7          1
90.        90         59          7          1
91.        91         60          8          0
92.        92         60          8          1
93.        93         61          8          1
94.        94         62          8          1
95.        95         62          8          1
96.        96         63          8          1
97.        97         64          8          0
98.        98         64          8          1
99.        99         65          8          1
100.       100         69          8          1 
Figure 1.1, page 4.
graph twoway scatter chd age, xlabel(20(10)70) ylabel(0(.2)1)
Table 1.2, page 4.
sort agrp
collapse (count) tot=chd (sum) present=chd, by(agrp)
gen prop = present / tot
gen absent = tot - present
gen count = present + absent
list agrp count absent present prop

agrp      count     absent    present       prop
1.         1         10          9          1         .1
2.         2         15         13          2   .1333333
3.         3         12          9          3        .25
4.         4         15         10          5   .3333333
5.         5         13          7          6   .4615385
6.         6          8          3          5       .625
7.         7         17          4         13   .7647059
8.         8         10          2          8         .8  
Figure 1.2, page 5.
graph twoway scatter prop agrp, ylabel(0(.2)1) xlabel(1(1)8)
Table 1.3, page 10.
use chdage.dta, clear
(Hosmer and Lemeshow - from chapter 1)

logistic chd age, coef

Logit estimates                                   Number of obs   =        100
LR chi2(1)      =      29.31
Prob > chi2     =     0.0000
Log likelihood = -53.676546                       Pseudo R2       =     0.2145

------------------------------------------------------------------------------
chd |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
age |   .1109211   .0240598     4.61   0.000     .0637647    .1580776
_cons |  -5.309453   1.133655    -4.68   0.000    -7.531376   -3.087531
------------------------------------------------------------------------------
or you could use
logit chd age

Iteration 0:   log likelihood = -68.331491
Iteration 1:   log likelihood = -54.170558
Iteration 2:   log likelihood = -53.681645
Iteration 3:   log likelihood = -53.676547
Iteration 4:   log likelihood = -53.676546

Logit estimates                                   Number of obs   =        100
LR chi2(1)      =      29.31
Prob > chi2     =     0.0000
Log likelihood = -53.676546                       Pseudo R2       =     0.2145

------------------------------------------------------------------------------
chd |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
age |   .1109211   .0240598     4.61   0.000     .0637647    .1580776
_cons |  -5.309453   1.133655    -4.68   0.000    -7.531376   -3.087531
------------------------------------------------------------------------------
Table 1.4, page 20.
* Stata 8 code.
vce

* Stata 9 code and output.
estat vce

Covariance matrix of coefficients of logit model

e(V) |        age       _cons
-------------+------------------------
age |  .00057888
_cons | -.02667702   1.2851728 

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