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Page 282 The coefficients in the middle of the page.
use http://www.ats.ucla.edu/stat/stata/examples/cama3/depress.dta, clear
logit cases age income
Iteration 0: log likelihood = -134.06225
Iteration 1: log likelihood = -127.42024
Iteration 2: log likelihood = -127.01794
Iteration 3: log likelihood = -127.01305
Iteration 4: log likelihood = -127.01304
Logit estimates Number of obs = 294
LR chi2(2) = 14.10
Prob > chi2 = 0.0009
Log likelihood = -127.01304 Pseudo R2 = 0.0526
------------------------------------------------------------------------------
cases | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
age | -.0201671 .0088966 -2.27 0.023 -.0376041 -.0027301
income | -.0413479 .0140587 -2.94 0.003 -.0689025 -.0137933
_cons | .0279774 .4872007 0.06 0.954 -.9269184 .9828732
------------------------------------------------------------------------------
Figure 12.1, page 283.
NOTE: We were unable to reproduce this graph.
Table 12.1, page 286.
tab sex cases
| depressed is cesd >=16
|
sex | normal depressed | Total
-----------+----------------------+----------
male | 101 10 | 111
female | 143 40 | 183
-----------+----------------------+----------
Total | 244 50 | 294
Page 286 The estimates at the bottom of the page.
gen sex1 = sex - 1
logit cases sex1
Iteration 0: log likelihood = -134.06225
Iteration 1: log likelihood = -129.83832
Iteration 2: log likelihood = -129.69929
Iteration 3: log likelihood = -129.69883
Logit estimates Number of obs = 294
LR chi2(1) = 8.73
Prob > chi2 = 0.0031
Log likelihood = -129.69883 Pseudo R2 = 0.0325
------------------------------------------------------------------------------
cases | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
sex1 | 1.03857 .3766834 2.76 0.006 .3002844 1.776856
_cons | -2.312535 .3315077 -6.98 0.000 -2.962279 -1.662792
------------------------------------------------------------------------------
Page 287 The odds ratios at the top of the page.
logit cases sex, or
Iteration 0: log likelihood = -134.06225
Iteration 1: log likelihood = -129.83832
Iteration 2: log likelihood = -129.69929
Iteration 3: log likelihood = -129.69883
Logit estimates Number of obs = 294
LR chi2(1) = 8.73
Prob > chi2 = 0.0031
Log likelihood = -129.69883 Pseudo R2 = 0.0325
------------------------------------------------------------------------------
cases | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
sex | 2.825175 1.064196 2.76 0.006 1.350243 5.911243
------------------------------------------------------------------------------
Page 288 Table of coefficients and standard errors.
logit cases age income
Iteration 0: log likelihood = -134.06225
Iteration 1: log likelihood = -127.42024
Iteration 2: log likelihood = -127.01794
Iteration 3: log likelihood = -127.01305
Iteration 4: log likelihood = -127.01304
Logit estimates Number of obs = 294
LR chi2(2) = 14.10
Prob > chi2 = 0.0009
Log likelihood = -127.01304 Pseudo R2 = 0.0526
------------------------------------------------------------------------------
cases | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
age | -.0201671 .0088966 -2.27 0.023 -.0376041 -.0027301
income | -.0413479 .0140587 -2.94 0.003 -.0689025 -.0137933
_cons | .0279774 .4872007 0.06 0.954 -.9269184 .9828732
------------------------------------------------------------------------------
Figure 12.2, page 294.
lsens
Figure 12.3, page 295.
lroc
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