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Polytomous logistic regression using the mammog file. We use the file below.
use mammog
Part of Table 8.2 -- page 222
tabulate me hist
| hist
me | 0 1 | Total
-----------+----------------------+----------
0 | 220 14 | 234
1 | 85 19 | 104
2 | 63 11 | 74
-----------+----------------------+----------
Total | 368 44 | 412
Table 8.3 -- page 223
mlogit me hist
Iteration 0: log likelihood = -402.59901
Iteration 1: log likelihood = -396.214
Iteration 2: log likelihood = -396.17
Iteration 3: log likelihood = -396.16997
Multinomial regression Number of obs = 412
LR chi2(2) = 12.86
Prob > chi2 = 0.0016
Log likelihood = -396.16997 Pseudo R2 = 0.0160
------------------------------------------------------------------------------
me | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
hist | 1.256358 .3746603 3.353 0.001 .5220372 1.990679
_cons | -.9509763 .1277112 -7.446 0.000 -1.201286 -.7006669
---------+--------------------------------------------------------------------
2 |
hist | 1.009331 .4274998 2.361 0.018 .1714466 1.847215
_cons | -1.250493 .1428932 -8.751 0.000 -1.530558 -.9704273
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
mlogit, rr
Iteration 0: log likelihood = -402.59901
Iteration 1: log likelihood = -396.214
Iteration 2: log likelihood = -396.17
Iteration 3: log likelihood = -396.16997
Multinomial regression Number of obs = 412
LR chi2(2) = 12.86
Prob > chi2 = 0.0016
Log likelihood = -396.16997 Pseudo R2 = 0.0160
------------------------------------------------------------------------------
me | RRR Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
hist | 3.512605 1.316034 3.353 0.001 1.685458 7.3205
---------+--------------------------------------------------------------------
2 |
hist | 2.743764 1.172959 2.361 0.018 1.187021 6.342131
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
Table 8.4 -- page 224
tabulate me detc
| detc
me | 1 2 3 | Total
-----------+---------------------------------+----------
0 | 13 77 144 | 234
1 | 1 12 91 | 104
2 | 4 16 54 | 74
-----------+---------------------------------+----------
Total | 18 105 289 | 412
Table 8.5 -- page 22
/* create dummy coding for variable detc */
xi i.detc
i.detc Idetc_1-3 (naturally coded; Idetc_1 omitted)
mlogit me Idetc_2 Idetc_3
Iteration 0: log likelihood = -402.59901
Iteration 1: log likelihood = -389.76354
Iteration 2: log likelihood = -389.21625
Iteration 3: log likelihood = -389.20061
Iteration 4: log likelihood = -389.20054
Multinomial regression Number of obs = 412
LR chi2(4) = 26.80
Prob > chi2 = 0.0000
Log likelihood = -389.20054 Pseudo R2 = 0.0333
------------------------------------------------------------------------------
me | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
Idetc_2 | .7060506 1.083136 0.652 0.514 -1.416856 2.828958
Idetc_3 | 2.105996 1.046325 2.013 0.044 .0552361 4.156755
_cons | -2.564949 1.03772 -2.472 0.013 -4.598843 -.5310556
---------+--------------------------------------------------------------------
2 |
Idetc_2 | -.3925617 .6343589 -0.619 0.536 -1.635882 .850759
Idetc_3 | .1978257 .5936221 0.333 0.739 -.9656522 1.361304
_cons | -1.178655 .5717729 -2.061 0.039 -2.299309 -.0580007
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
mlogit, rr
Iteration 0: log likelihood = -402.59901
Iteration 1: log likelihood = -389.76354
Iteration 2: log likelihood = -389.21625
Iteration 3: log likelihood = -389.20061
Iteration 4: log likelihood = -389.20054
Multinomial regression Number of obs = 412
LR chi2(4) = 26.80
Prob > chi2 = 0.0000
Log likelihood = -389.20054 Pseudo R2 = 0.0333
------------------------------------------------------------------------------
me | RRR Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
Idetc_2 | 2.025974 2.194405 0.652 0.514 .2424751 16.92781
Idetc_3 | 8.215278 8.595851 2.013 0.044 1.05679 63.86395
---------+--------------------------------------------------------------------
2 |
Idetc_2 | .6753247 .4283982 -0.619 0.536 .1947804 2.341423
Idetc_3 | 1.21875 .7234769 0.333 0.739 .3807348 3.901276
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
Table 8.6 -- page 227
/* create dummy coding for the variable sympt */
xi i.detc i.sympt
i.detc Idetc_1-3 (naturally coded; Idetc_1 omitted)
i.sympt Isympt_1-4 (naturally coded; Isympt_1 omitted)
mlogit me Isympt_2 Isympt_3 Isympt_4 pb hist bse Idetc_2 Idetc_3
Iteration 0: log likelihood = -402.59901
Iteration 1: log likelihood = -351.59713
Iteration 2: log likelihood = -347.26545
Iteration 3: log likelihood = -346.95451
Iteration 4: log likelihood = -346.95096
Iteration 5: log likelihood = -346.95096
Multinomial regression Number of obs = 412
LR chi2(16) = 111.30
Prob > chi2 = 0.0000
Log likelihood = -346.95096 Pseudo R2 = 0.1382
------------------------------------------------------------------------------
me | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
Isympt_2 | .1100372 .9227608 0.119 0.905 -1.698541 1.918615
Isympt_3 | 1.924708 .7775975 2.475 0.013 .4006449 3.448771
Isympt_4 | 2.456993 .7753323 3.169 0.002 .9373693 3.976616
pb | -.2194368 .0755139 -2.906 0.004 -.3674414 -.0714323
hist | 1.366239 .4375196 3.123 0.002 .5087163 2.223762
bse | 1.291666 .529891 2.438 0.015 .2530992 2.330234
Idetc_2 | .0170207 1.161896 0.015 0.988 -2.260254 2.294296
Idetc_3 | .9041379 1.126822 0.802 0.422 -1.304393 3.112668
_cons | -2.99875 1.53922 -1.948 0.051 -6.015566 .0180663
---------+--------------------------------------------------------------------
2 |
Isympt_2 | -.2900833 .6440636 -0.450 0.652 -1.552425 .9722582
Isympt_3 | .8173136 .5397922 1.514 0.130 -.2406596 1.875287
Isympt_4 | 1.132239 .5476704 2.067 0.039 .0588252 2.205654
pb | -.1482068 .0763686 -1.941 0.052 -.2978866 .0014729
hist | 1.065436 .459396 2.319 0.020 .1650366 1.965836
bse | 1.052144 .5149894 2.043 0.041 .0427838 2.061505
Idetc_2 | -.9243928 .7137382 -1.295 0.195 -2.323294 .4745083
Idetc_3 | -.6905329 .6871078 -1.005 0.315 -2.037239 .6561736
_cons | -.9860915 1.111832 -0.887 0.375 -3.165242 1.193059
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
Table 8.7 -- page 229
/* create dummy variable for the variable sympt */
generate sympd = (sympt>=3)
mlogit me sympd pb hist bse Idetc_2 Idetc_3
Iteration 0: log likelihood = -402.59901
Iteration 1: log likelihood = -353.37799
Iteration 2: log likelihood = -349.07042
Iteration 3: log likelihood = -348.75167
Iteration 4: log likelihood = -348.74797
Iteration 5: log likelihood = -348.74797
Multinomial regression Number of obs = 412
LR chi2(12) = 107.70
Prob > chi2 = 0.0000
Log likelihood = -348.74797 Pseudo R2 = 0.1338
------------------------------------------------------------------------------
me | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
sympd | 2.095341 .4573977 4.581 0.000 1.198858 2.991824
pb | -.2510121 .0729327 -3.442 0.001 -.3939575 -.1080667
hist | 1.293281 .4335351 2.983 0.003 .4435676 2.142994
bse | 1.243974 .5263057 2.364 0.018 .212434 2.275514
Idetc_2 | .0902755 1.161025 0.078 0.938 -2.185291 2.365842
Idetc_3 | .9728148 1.126271 0.864 0.388 -1.234636 3.180266
_cons | -2.70375 1.434414 -1.885 0.059 -5.51515 .1076495
---------+--------------------------------------------------------------------
2 |
sympd | 1.121365 .3571979 3.139 0.002 .4212698 1.82146
pb | -.1681062 .0741724 -2.266 0.023 -.3134815 -.022731
hist | 1.014055 .4538042 2.235 0.025 .1246154 1.903495
bse | 1.02859 .5139737 2.001 0.045 .0212205 2.035961
Idetc_2 | -.9021325 .7146177 -1.262 0.207 -2.302758 .4984924
Idetc_3 | -.6698221 .687579 -0.974 0.330 -2.017452 .6778079
_cons | -.9987682 1.071963 -0.932 0.351 -3.099778 1.102242
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
Table 8.11 -- page 237
/* create indicator for covariate patterns to drop */
generate dr=1
replace dr=0 if sympd==1 & pb==9 & hist==0 & bse==1 & detc==3 & me~=2
(18 real changes made)
replace dr=0 if sympd==1 & pb==10 & hist==0 & bse==1 & detc==3 & me~=1
(19 real changes made)
mlogit me sympd pb hist bse Idetc_2 Idetc_3 if dr
Iteration 0: log likelihood = -370.25296
Iteration 1: log likelihood = -321.13834
Iteration 2: log likelihood = -316.98409
Iteration 3: log likelihood = -316.69093
Iteration 4: log likelihood = -316.68774
Iteration 5: log likelihood = -316.68774
Multinomial regression Number of obs = 375
LR chi2(12) = 107.13
Prob > chi2 = 0.0000
Log likelihood = -316.68774 Pseudo R2 = 0.1447
------------------------------------------------------------------------------
me | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------+--------------------------------------------------------------------
1 |
sympd | 2.12008 .4626308 4.583 0.000 1.21334 3.02682
pb | -.2239193 .0863309 -2.594 0.009 -.3931248 -.0547139
hist | 1.284491 .4361839 2.945 0.003 .4295861 2.139396
bse | 1.272927 .5322003 2.392 0.017 .2298336 2.31602
Idetc_2 | .126428 1.161566 0.109 0.913 -2.150199 2.403055
Idetc_3 | 1.051825 1.134602 0.927 0.354 -1.171954 3.275605
_cons | -2.998474 1.527725 -1.963 0.050 -5.992761 -.0041876
---------+--------------------------------------------------------------------
2 |
sympd | 1.276385 .3608517 3.537 0.000 .569129 1.983642
pb | -.0801428 .0789808 -1.015 0.310 -.2349423 .0746566
hist | .8973055 .455521 1.970 0.049 .0045008 1.79011
bse | 1.190551 .517193 2.302 0.021 .1768715 2.204231
Idetc_2 | -.8124063 .7112956 -1.142 0.253 -2.20652 .5817074
Idetc_3 | -.3647423 .691984 -0.527 0.598 -1.721006 .9915215
_cons | -2.029162 1.147398 -1.768 0.077 -4.27802 .219697
------------------------------------------------------------------------------
(Outcome me==0 is the comparison group)
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