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The first example in this chapter makes use of the lowbwt.dta file.
use lowbwt
Table 4.2 -- page 93 (output edited for space)
/* create dummy variable for the variable race */
xi i.race
i.race Irace_1-3 (naturally coded; Irace_1 omitted)
logit low
Logit estimates Number of obs = 189
LR chi2(0) = 0.00
Prob > chi2 = .
Log likelihood = -117.336 Pseudo R2 = 0.0000
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
_cons | -.789997 .156976 -5.033 0.000 -1.097664 -.4823297
------------------------------------------------------------------------------
logit low age
Logit estimates Number of obs = 189
LR chi2(1) = 2.76
Prob > chi2 = 0.0966
Log likelihood = -115.95598 Pseudo R2 = 0.0118
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
age | -.0511529 .0315138 -1.623 0.105 -.1129188 .0106129
_cons | .3845819 .7321251 0.525 0.599 -1.050357 1.819521
------------------------------------------------------------------------------
logit low age, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
age | .9501333 .0299423 -1.623 0.105 .8932232 1.010669
------------------------------------------------------------------------------
logit low lwt
Logit estimates Number of obs = 189
LR chi2(1) = 5.98
Prob > chi2 = 0.0145
Log likelihood = -114.34533 Pseudo R2 = 0.0255
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
lwt | -.0140583 .0061696 -2.279 0.023 -.0261504 -.0019661
_cons | .9983143 .7852889 1.271 0.204 -.5408235 2.537452
------------------------------------------------------------------------------
logit low lwt, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
lwt | .9860401 .0060834 -2.279 0.023 .9741886 .9980358
------------------------------------------------------------------------------
logit low Irace_2
Logit estimates Number of obs = 189
LR chi2(1) = 1.65
Prob > chi2 = 0.1985
Log likelihood = -116.50935 Pseudo R2 = 0.0070
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
Irace_2 | .5635762 .4325561 1.303 0.193 -.2842181 1.41137
_cons | -.8737311 .17184 -5.085 0.000 -1.210531 -.5369309
------------------------------------------------------------------------------
logit low Irace_2, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
Irace_2 | 1.756944 .759977 1.303 0.193 .7526025 4.101573
------------------------------------------------------------------------------
logit low Irace_3
Logit estimates Number of obs = 189
LR chi2(1) = 1.77
Prob > chi2 = 0.1829
Log likelihood = -116.44906 Pseudo R2 = 0.0076
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
Irace_3 | .4321825 .3233953 1.336 0.181 -.2016606 1.066026
_cons | -.9509763 .2019289 -4.709 0.000 -1.34675 -.5552028
------------------------------------------------------------------------------
logit low Irace_3, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
Irace_3 | 1.540616 .498228 1.336 0.181 .8173723 2.903816
------------------------------------------------------------------------------
logit low smoke
Logit estimates Number of obs = 189
LR chi2(1) = 4.87
Prob > chi2 = 0.0274
Log likelihood = -114.9023 Pseudo R2 = 0.0207
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
smoke | .7040592 .3196386 2.203 0.028 .0775791 1.330539
_cons | -1.087051 .2147299 -5.062 0.000 -1.507914 -.6661886
------------------------------------------------------------------------------
logit low smoke, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
smoke | 2.021944 .6462912 2.203 0.028 1.080668 3.783083
------------------------------------------------------------------------------
logit low ptl
Logit estimates Number of obs = 189
LR chi2(1) = 6.78
Prob > chi2 = 0.0092
Log likelihood = -113.94631 Pseudo R2 = 0.0289
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ptl | .8018058 .3171535 2.528 0.011 .1801964 1.423415
_cons | -.964189 .1749607 -5.511 0.000 -1.307106 -.6212722
------------------------------------------------------------------------------
logit low ptl, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ptl | 2.229563 .7071138 2.528 0.011 1.197453 4.151274
------------------------------------------------------------------------------
logit low ht
Logit estimates Number of obs = 189
LR chi2(1) = 4.02
Prob > chi2 = 0.0449
Log likelihood = -115.32493 Pseudo R2 = 0.0171
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ht | 1.213542 .6083485 1.995 0.046 .0212011 2.405883
_cons | -.87707 .1650175 -5.315 0.000 -1.200498 -.5536417
------------------------------------------------------------------------------
logit low ht, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ht | 3.365385 2.047327 1.995 0.046 1.021427 11.08822
------------------------------------------------------------------------------
logit low ui
Logit estimates Number of obs = 189
LR chi2(1) = 5.08
Prob > chi2 = 0.0243
Log likelihood = -114.79795 Pseudo R2 = 0.0216
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ui | .9469277 .4167734 2.272 0.023 .1300669 1.763789
_cons | -.9469277 .1756215 -5.392 0.000 -1.29114 -.6027159
------------------------------------------------------------------------------
logit low ui, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ui | 2.577778 1.074349 2.272 0.023 1.138905 5.8345
------------------------------------------------------------------------------
logit low ftv
Logit estimates Number of obs = 189
LR chi2(1) = 0.77
Prob > chi2 = 0.3792
Log likelihood = -116.94943 Pseudo R2 = 0.0033
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ftv | -.1351199 .1566986 -0.862 0.389 -.4422435 .1720037
_cons | -.6867585 .1948119 -3.525 0.000 -1.068583 -.3049343
------------------------------------------------------------------------------
logit low ftv, or
------------------------------------------------------------------------------
low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
ftv | .8736112 .1368936 -0.862 0.389 .6425932 1.187682
------------------------------------------------------------------------------
Table 4.3 -- page 94
logit low age lwt Irace_2 Irace_3 smoke ptl ht ui
Iteration 0: log likelihood = -117.336
Iteration 1: log likelihood = -101.38735
Iteration 2: log likelihood = -100.72104
Iteration 3: log likelihood = -100.71348
Iteration 4: log likelihood = -100.71348
Logit estimates Number of obs = 189
LR chi2(8) = 33.25
Prob > chi2 = 0.0001
Log likelihood = -100.71348 Pseudo R2 = 0.1417
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
age | -.0270698 .0364526 -0.743 0.458 -.0985156 .044376
lwt | -.0151826 .0069279 -2.192 0.028 -.028761 -.0016041
Irace_2 | 1.263219 .5264677 2.399 0.016 .2313616 2.295077
Irace_3 | .8616351 .4391975 1.962 0.050 .0008239 1.722446
smoke | .9233492 .4008583 2.303 0.021 .1376813 1.709017
ptl | .5417551 .3462666 1.565 0.118 -.1369149 1.220425
ht | 1.833696 .69177 2.651 0.008 .4778514 3.18954
ui | .7585965 .4593918 1.651 0.099 -.1417949 1.658988
_cons | .4644033 1.204702 0.385 0.700 -1.896769 2.825576
------------------------------------------------------------------------------
Table 4.4 -- page 95
logit low lwt Irace_2 Irace_3 smoke ptl ht ui
Iteration 0: log likelihood = -117.336
Iteration 1: log likelihood = -101.58398
Iteration 2: log likelihood = -100.99797
Iteration 3: log likelihood = -100.99279
Iteration 4: log likelihood = -100.99279
Logit estimates Number of obs = 189
LR chi2(7) = 32.69
Prob > chi2 = 0.0000
Log likelihood = -100.99279 Pseudo R2 = 0.1393
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
lwt | -.0159053 .0068553 -2.320 0.020 -.0293414 -.0024691
Irace_2 | 1.325719 .5222464 2.538 0.011 .3021351 2.349304
Irace_3 | .8970779 .4338846 2.068 0.039 .0466797 1.747476
smoke | .9387268 .3987195 2.354 0.019 .1572509 1.720203
ptl | .5032149 .3412323 1.475 0.140 -.1655881 1.172018
ht | 1.855042 .6951214 2.669 0.008 .4926286 3.217455
ui | .7856975 .4564423 1.721 0.085 -.108913 1.680308
_cons | -.0865495 .951768 -0.091 0.928 -1.951981 1.778882
------------------------------------------------------------------------------
Table 4.8 -- page 98
/* create dichotomous variable for pptl and lwt */
generate lwd = (lwt<110)
generate ptd = (ptl~=0)
logit low age lwd Irace_2 Irace_3 smoke ptd ht ui
Iteration 0: log likelihood = -117.336
Iteration 1: log likelihood = -99.431174
Iteration 2: log likelihood = -98.785718
Iteration 3: log likelihood = -98.778
Iteration 4: log likelihood = -98.777998
Logit estimates Number of obs = 189
LR chi2(8) = 37.12
Prob > chi2 = 0.0000
Log likelihood = -98.777998 Pseudo R2 = 0.1582
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
age | -.0464796 .0373888 -1.243 0.214 -.1197603 .0268011
lwd | .8420615 .4055338 2.076 0.038 .0472299 1.636893
Irace_2 | 1.073456 .5150752 2.084 0.037 .0639273 2.082985
Irace_3 | .815367 .4452979 1.831 0.067 -.0574008 1.688135
smoke | .8071996 .404446 1.996 0.046 .0145001 1.599899
ptd | 1.281678 .4621157 2.774 0.006 .3759478 2.187408
ht | 1.435227 .6482699 2.214 0.027 .1646415 2.705813
ui | .6576256 .4666192 1.409 0.159 -.2569313 1.572182
_cons | -1.216781 .9556797 -1.273 0.203 -3.089878 .656317
------------------------------------------------------------------------------
Table 4.10 -- page 101
/* create interaction variables */
generate agelwd=age*lwd
generate smokelwd=smoke*lwd
logit low age Irace_2 Irace_3 smoke ht ui lwd ptd agelwd smokelwd
Iteration 0: log likelihood = -117.336
Iteration 1: log likelihood = -97.135228
Iteration 2: log likelihood = -96.03855
Iteration 3: log likelihood = -96.006202
Iteration 4: log likelihood = -96.00616
Logit estimates Number of obs = 189
LR chi2(10) = 42.66
Prob > chi2 = 0.0000
Log likelihood = -96.00616 Pseudo R2 = 0.1818
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
age | -.0839782 .0455663 -1.843 0.065 -.1732864 .0053301
Irace_2 | 1.083103 .5189153 2.087 0.037 .0660474 2.100158
Irace_3 | .7596787 .4640335 1.637 0.102 -.1498103 1.669168
smoke | 1.153131 .4584383 2.515 0.012 .2546084 2.051653
ht | 1.359216 .661471 2.055 0.040 .062757 2.655676
ui | .7281685 .4794797 1.519 0.129 -.2115945 1.667932
lwd | -1.729949 1.868306 -0.926 0.354 -5.391762 1.931863
ptd | 1.231578 .4713903 2.613 0.009 .3076701 2.155486
agelwd | .1474112 .0828594 1.779 0.075 -.0149902 .3098127
smokelwd | -1.407375 .8186761 -1.719 0.086 -3.011951 .1972003
_cons | -.5117544 1.087536 -0.471 0.638 -2.643286 1.619777
------------------------------------------------------------------------------
Table 4.15 -- page 113
* Stata 8 code.
sw logit low ptl lwt ht (Irace_2 Irace_3) smoke ui age ftv, pe(.15) pr(.2) forward
* Stata 9 code and output.
stepwise, pe(.15) pr(.2) forward: logit low ptl lwt ht (Irace_2 Irace_3) smoke ui age ftv
begin with empty model
p = 0.0115 < 0.1500 adding ptl
p = 0.0388 < 0.1500 adding ht
p = 0.0105 < 0.1500 adding lwt
p = 0.0784 < 0.1500 adding _Irace_2 _Irace_3
p = 0.0166 < 0.1500 adding smoke
p = 0.0852 < 0.1500 adding ui
Logistic regression Number of obs = 189
LR chi2(7) = 32.69
Prob > chi2 = 0.0000
Log likelihood = -100.99279 Pseudo R2 = 0.1393
------------------------------------------------------------------------------
low | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ptl | .5032149 .3412323 1.47 0.140 -.1655881 1.172018
ht | 1.855042 .6951214 2.67 0.008 .4926286 3.217455
lwt | -.0159053 .0068553 -2.32 0.020 -.0293414 -.0024691
Irace_2 | 1.325719 .5222464 2.54 0.011 .3021351 2.349304
Irace_3 | .8970779 .4338846 2.07 0.039 .0466797 1.747476
smoke | .9387268 .3987195 2.35 0.019 .1572509 1.720203
ui | .7856975 .4564423 1.72 0.085 -.108913 1.680308
_cons | -.0865495 .951768 -0.09 0.928 -1.951981 1.778882
------------------------------------------------------------------------------
The final example in this chapter makes use of the ex4-24.dta file.
use ex4-24
Table 4.24 -- page 132
list
id y x1 x2 x3
1. 1 0 .225 .231 1.026
2. 2 1 .487 .489 1.022
3. 3 0 -1.08 -1.07 1.074
4. 4 0 -.87 -.87 1.091
5. 5 0 -.58 -.57 1.095
6. 6 0 -.64 -.64 1.01
7. 7 0 1.614 1.619 1.087
8. 8 1 .352 .355 1.095
9. 9 0 -1.025 -1.018 1.008
10. 10 1 .929 .937 1.057
Table 4.24 -- page 132
The values of the coefficients in this table differ from those in the book due to the precision of the representation of the data and to differences in the maximum likelihood algorithms.
logit y x1
Iteration 0: log likelihood = -6.108643
Iteration 1: log likelihood = -4.9146936
Iteration 2: log likelihood = -4.8717399
Iteration 3: log likelihood = -4.8713285
Iteration 4: log likelihood = -4.8713284
Logit estimates Number of obs = 10
LR chi2(1) = 2.47
Prob > chi2 = 0.1157
Log likelihood = -4.8713284 Pseudo R2 = 0.2026
------------------------------------------------------------------------------
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x1 | 1.380311 1.005368 1.373 0.170 -.5901735 3.350795
_cons | -1.001712 .8294342 -1.208 0.227 -2.627373 .6239494
------------------------------------------------------------------------------
logit y x1 x2
Iteration 0: log likelihood = -6.108643
Iteration 1: log likelihood = -4.8196088
Iteration 2: log likelihood = -4.7259858
Iteration 3: log likelihood = -4.7212724
Iteration 4: log likelihood = -4.721251
Logit estimates Number of obs = 10
LR chi2(2) = 2.77
Prob > chi2 = 0.2497
Log likelihood = -4.721251 Pseudo R2 = 0.2271
------------------------------------------------------------------------------
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x1 | 146.395 276.9998 0.529 0.597 -396.5147 689.3047
x2 | -144.9098 276.6344 -0.524 0.600 -687.1033 397.2836
_cons | -.3703049 1.362457 -0.272 0.786 -3.040672 2.300062
------------------------------------------------------------------------------
logit y x3
Iteration 0: log likelihood = -6.108643
Iteration 1: log likelihood = -6.104626
Iteration 2: log likelihood = -6.1046254
Logit estimates Number of obs = 10
LR chi2(1) = 0.01
Prob > chi2 = 0.9286
Log likelihood = -6.1046254 Pseudo R2 = 0.0007
------------------------------------------------------------------------------
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x3 | 1.787782 19.97092 0.090 0.929 -37.35449 40.93006
_cons | -2.736861 21.12781 -0.130 0.897 -44.1466 38.67288
------------------------------------------------------------------------------
logit y x1 x2 x3
Iteration 0: log likelihood = -6.108643
Iteration 1: log likelihood = -4.8146158
Iteration 2: log likelihood = -4.7162391
Iteration 3: log likelihood = -4.71065
Iteration 4: log likelihood = -4.7106177
Logit estimates Number of obs = 10
LR chi2(3) = 2.80
Prob > chi2 = 0.4242
Log likelihood = -4.7106177 Pseudo R2 = 0.2289
------------------------------------------------------------------------------
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
x1 | 142.9769 282.1838 0.507 0.612 -410.0932 696.047
x2 | -141.4593 281.832 -0.502 0.616 -693.8398 410.9212
x3 | -3.621109 24.95384 -0.145 0.885 -52.52974 45.28752
_cons | 3.42313 26.1558 0.131 0.896 -47.8413 54.68756
------------------------------------------------------------------------------
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