log type: text
opened on: 31 Oct 2005, 18:32:24
. use "C:\Documents and Settings\Michael Rosenfeld\My Documents\current class file
> s\methods tabular arrays\HW3 dataset with best fit vars.dta", clear
. poisson count
Iteration 0: log likelihood = -2252613.6
Iteration 1: log likelihood = -2252613.6
Poisson regression Number of obs = 225
LR chi2(0) = 0.00
Prob > chi2 = .
Log likelihood = -2252613.6 Pseudo R2 = 0.0000
------------------------------------------------------------------------------
count | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_cons | 7.968352 .0012405 6423.41 0.000 7.96592 7.970783
------------------------------------------------------------------------------
. poisgof
Goodness-of-fit chi2 = 4503895
Prob > chi2(224) = 0.0000
. tabulate year [fweight=count]
year | Freq. Percent Cum.
------------+-----------------------------------
70 | 64,903 9.99 9.99
80 | 348,247 53.59 63.58
90 | 236,671 36.42 100.00
------------+-----------------------------------
Total | 649,821 100.00
. predict P_const
(option n assumed; predicted number of events)
. gen ID_const=50*(abs((P_const/649821)-(count/649821)))
. table year, contents(sum ID_const) col
-------------------------
year | sum(ID_const)
----------+--------------
70 | 19.85205
80 | 37.27435
90 | 29.0707
-------------------------
. table year, contents(sum ID_const) row
-------------------------
year | sum(ID_const)
----------+--------------
70 | 19.85205
80 | 37.27435
90 | 29.0707
|
Total | 86.1971
-------------------------
. desmat: poisson count year*meth year*feth
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -790561.144
LR chi square: 2924105.006
Model degrees of freedom: 26
Pseudo R-squared: 0.649
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 1.759** 0.022
2 90 0.807** 0.023
meth
3 Mex_Am -1.346** 0.032
4 Oth_H -1.192** 0.030
5 Oth_NH -2.330** 0.049
6 Wht_NH 2.483** 0.015
year.meth
7 80.Mex_Am 0.634** 0.034
8 80.Oth_H -0.406** 0.034
9 80.Oth_NH 0.446** 0.051
10 80.Wht_NH -0.079** 0.016
11 90.Mex_Am 1.092** 0.034
12 90.Oth_H 0.105** 0.034
13 90.Oth_NH 0.959** 0.052
14 90.Wht_NH 0.198** 0.017
feth
15 Mex_Am -1.364** 0.032
16 Oth_H -1.184** 0.030
17 Oth_NH -2.145** 0.045
18 Wht_NH 2.496** 0.015
year.feth
19 80.Mex_Am 0.656** 0.034
20 80.Oth_H -0.393** 0.034
21 80.Oth_NH 0.537** 0.048
22 80.Wht_NH -0.046** 0.017
23 90.Mex_Am 1.165** 0.035
24 90.Oth_H 0.172** 0.035
25 90.Oth_NH 1.048** 0.048
26 90.Wht_NH 0.248** 0.018
27 _cons 4.744** 0.020
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 1579790
Prob > chi2(198) = 0.0000
. set linesize 79
. predict P2
(option n assumed; predicted number of events)
. gen ID2=50*(abs((P2/649821)-(count/649821)))
. table year, contents(sum ID_const) row
-------------------------
year | sum(ID_const)
----------+--------------
70 | 19.85205
80 | 37.27435
90 | 29.0707
|
Total | 86.1971
-------------------------
. table year, contents(sum ID2) row
----------------------
year | sum(ID2)
----------+-----------
70 | 6.827739
80 | 35.90606
90 | 23.68337
|
Total | 66.41717
----------------------
. desmat: poisson count year*meth*mgen year*feth*fgen
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -227495.013
LR chi square: 4050237.268
Model degrees of freedom: 56
Pseudo R-squared: 0.899
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.212** 0.330
2 90 4.275** 0.331
meth
3 Mex_Am 1.418** 0.200
4 Oth_H 1.248** 0.204
5 Oth_NH 0.255 0.239
6 Wht_NH 3.252** 0.183
year.meth
7 80.Mex_Am 0.149 0.207
8 80.Oth_H 0.072 0.211
9 80.Oth_NH 0.055 0.247
10 80.Wht_NH -0.776** 0.190
11 90.Mex_Am 0.341 0.208
12 90.Oth_H 0.069 0.212
13 90.Oth_NH 0.154 0.248
14 90.Wht_NH -0.942** 0.191
mgen
15 US native 5.004** 0.180
year.mgen
16 80.US native -0.936** 0.186
17 90.US native -1.496** 0.187
meth.mgen
18 Mex_Am.US native -2.866** 0.203
19 Oth_H.US native -2.511** 0.206
20 Oth_NH.US native -2.669** 0.245
21 Wht_NH.US native -0.777** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.430* 0.210
23 80.Oth_H.US native -0.750** 0.214
24 80.Oth_NH.US native 0.333 0.253
25 80.Wht_NH.US native 0.704** 0.190
26 90.Mex_Am.US native 0.645** 0.211
27 90.Oth_H.US native -0.237 0.215
28 90.Oth_NH.US native 0.735** 0.254
29 90.Wht_NH.US native 1.157** 0.191
feth
30 Mex_Am 2.148** 0.282
31 Oth_H 1.894** 0.287
32 Oth_NH 2.148** 0.282
33 Wht_NH 4.377** 0.269
year.feth
34 80.Mex_Am -0.912** 0.289
35 80.Oth_H -0.625* 0.293
36 80.Oth_NH -0.671* 0.289
37 80.Wht_NH -1.636** 0.275
38 90.Mex_Am -0.653* 0.290
39 90.Oth_H -0.394 0.294
40 90.Oth_NH -0.596* 0.290
41 90.Wht_NH -1.765** 0.276
fgen
42 US native 5.796** 0.268
year.fgen
43 80.US native -1.538** 0.273
44 90.US native -2.014** 0.274
feth.fgen
45 Mex_Am.US native -3.615** 0.284
46 Oth_H.US native -3.141** 0.288
47 Oth_NH.US native -4.537** 0.287
48 Wht_NH.US native -1.898** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.585** 0.291
50 80.Oth_H.US native 0.043 0.295
51 80.Oth_NH.US native 1.114** 0.293
52 80.Wht_NH.US native 1.601** 0.275
53 90.Mex_Am.US native 1.819** 0.292
54 90.Oth_H.US native 0.344 0.296
55 90.Oth_NH.US native 1.548** 0.295
56 90.Wht_NH.US native 2.033** 0.277
57 _cons -4.967** 0.322
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 453658
Prob > chi2(168) = 0.0000
. predict P3
(option n assumed; predicted number of events)
. gen ID3=50*(abs((P3/649821)-(count/649821)))
. table year, contents(sum ID3) row
----------------------
year | sum(ID3)
----------+-----------
70 | 1.944655
80 | 10.98952
90 | 6.745275
|
Total | 19.67946
----------------------
. desmat: poisson count year*meth*mgen year*feth*fgen BW MOh
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -100679.856
LR chi square: 4303867.583
Model degrees of freedom: 58
Pseudo R-squared: 0.955
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.162** 0.330
2 90 4.454** 0.332
meth
3 Mex_Am -0.024 0.201
4 Oth_H -0.191 0.205
5 Oth_NH -1.171** 0.240
6 Wht_NH 2.049** 0.185
year.meth
7 80.Mex_Am 0.133 0.208
8 80.Oth_H 0.037 0.212
9 80.Oth_NH 0.032 0.248
10 80.Wht_NH -0.815** 0.191
11 90.Mex_Am 0.250 0.209
12 90.Oth_H -0.046 0.213
13 90.Oth_NH 0.059 0.249
14 90.Wht_NH -1.088** 0.192
mgen
15 US native 5.009** 0.180
year.mgen
16 80.US native -0.958** 0.186
17 90.US native -1.539** 0.187
meth.mgen
18 Mex_Am.US native -2.869** 0.203
19 Oth_H.US native -2.514** 0.206
20 Oth_NH.US native -2.670** 0.245
21 Wht_NH.US native -0.782** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.451* 0.210
23 80.Oth_H.US native -0.729** 0.214
24 80.Oth_NH.US native 0.355 0.253
25 80.Wht_NH.US native 0.728** 0.190
26 90.Mex_Am.US native 0.685** 0.211
27 90.Oth_H.US native -0.196 0.215
28 90.Oth_NH.US native 0.778** 0.254
29 90.Wht_NH.US native 1.202** 0.191
feth
30 Mex_Am 0.751** 0.283
31 Oth_H 0.499 0.287
32 Oth_NH 0.767** 0.283
33 Wht_NH 3.232** 0.270
year.feth
34 80.Mex_Am -0.829** 0.290
35 80.Oth_H -0.560 0.294
36 80.Oth_NH -0.596* 0.289
37 80.Wht_NH -1.543** 0.276
38 90.Mex_Am -0.671* 0.291
39 90.Oth_H -0.433 0.295
40 90.Oth_NH -0.619* 0.291
41 90.Wht_NH -1.815** 0.277
fgen
42 US native 5.795** 0.268
year.fgen
43 80.US native -1.555** 0.273
44 90.US native -2.054** 0.274
feth.fgen
45 Mex_Am.US native -3.614** 0.284
46 Oth_H.US native -3.140** 0.288
47 Oth_NH.US native -4.534** 0.287
48 Wht_NH.US native -1.897** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.601** 0.291
50 80.Oth_H.US native 0.059 0.295
51 80.Oth_NH.US native 1.132** 0.293
52 80.Wht_NH.US native 1.620** 0.275
53 90.Mex_Am.US native 1.857** 0.292
54 90.Oth_H.US native 0.381 0.296
55 90.Oth_NH.US native 1.589** 0.295
56 90.Wht_NH.US native 2.076** 0.277
BW
57 1 -4.613** 0.020
MOh
58 1 0.747** 0.030
59 _cons -2.535** 0.322
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 200027.7
Prob > chi2(166) = 0.0000
. predict P4
(option n assumed; predicted number of events)
. gen ID4=50*(abs((P4/649821)-(count/649821)))
. table year, contents(sum ID4) row
----------------------
year | sum(ID4)
----------+-----------
70 | .7162559
80 | 4.355475
90 | 3.422688
|
Total | 8.494419
----------------------
. desmat: poisson count year*meth*mgen year*feth*fgen ethintdm
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -14085.822
LR chi square: 4477055.651
Model degrees of freedom: 57
Pseudo R-squared: 0.994
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.180** 0.330
2 90 4.502** 0.332
meth
3 Mex_Am 2.065** 0.203
4 Oth_H 1.780** 0.206
5 Oth_NH 1.173** 0.242
6 Wht_NH 2.070** 0.184
year.meth
7 80.Mex_Am -0.153 0.210
8 80.Oth_H 0.304 0.213
9 80.Oth_NH -0.172 0.250
10 80.Wht_NH -0.833** 0.191
11 90.Mex_Am -0.212 0.210
12 90.Oth_H 0.066 0.214
13 90.Oth_NH -0.296 0.251
14 90.Wht_NH -1.138** 0.192
mgen
15 US native 5.017** 0.180
year.mgen
16 80.US native -0.946** 0.186
17 90.US native -1.514** 0.187
meth.mgen
18 Mex_Am.US native -2.942** 0.203
19 Oth_H.US native -2.561** 0.206
20 Oth_NH.US native -2.815** 0.245
21 Wht_NH.US native -0.787** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.430* 0.210
23 80.Oth_H.US native -0.900** 0.214
24 80.Oth_NH.US native 0.235 0.254
25 80.Wht_NH.US native 0.719** 0.190
26 90.Mex_Am.US native 0.625** 0.211
27 90.Oth_H.US native -0.431* 0.215
28 90.Oth_NH.US native 0.619* 0.254
29 90.Wht_NH.US native 1.184** 0.191
feth
30 Mex_Am 2.788** 0.284
31 Oth_H 2.470** 0.288
32 Oth_NH 3.204** 0.284
33 Wht_NH 3.243** 0.270
year.feth
34 80.Mex_Am -1.089** 0.291
35 80.Oth_H -0.250 0.295
36 80.Oth_NH -0.672* 0.291
37 80.Wht_NH -1.539** 0.276
38 90.Mex_Am -0.940** 0.292
39 90.Oth_H -0.182 0.296
40 90.Oth_NH -0.770** 0.292
41 90.Wht_NH -1.801** 0.277
fgen
42 US native 5.802** 0.268
year.fgen
43 80.US native -1.541** 0.273
44 90.US native -2.023** 0.274
feth.fgen
45 Mex_Am.US native -3.691** 0.285
46 Oth_H.US native -3.195** 0.288
47 Oth_NH.US native -4.590** 0.287
48 Wht_NH.US native -1.902** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.530** 0.291
50 80.Oth_H.US native -0.158 0.295
51 80.Oth_NH.US native 1.057** 0.294
52 80.Wht_NH.US native 1.611** 0.275
53 90.Mex_Am.US native 1.717** 0.292
54 90.Oth_H.US native 0.120 0.297
55 90.Oth_NH.US native 1.473** 0.295
56 90.Wht_NH.US native 2.055** 0.277
ethintdm
57 1 3.218** 0.006
58 _cons -5.767** 0.322
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 26839.64
Prob > chi2(167) = 0.0000
. predict P5
(option n assumed; predicted number of events)
. gen ID5=50*(abs((P5/649821)-(count/649821)))
. table year, contents(sum ID5) row
----------------------
year | sum(ID5)
----------+-----------
70 | .2679835
80 | 1.430308
90 | 1.244289
|
Total | 2.94258
----------------------
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -3201.028
LR chi square: 4498825.239
Model degrees of freedom: 61
Pseudo R-squared: 0.999
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.172** 0.330
2 90 4.515** 0.332
meth
3 Mex_Am 3.643** 0.208
4 Oth_H 3.607** 0.211
5 Oth_NH 3.070** 0.245
6 Wht_NH 4.073** 0.191
year.meth
7 80.Mex_Am -0.421 0.215
8 80.Oth_H -0.033 0.218
9 80.Oth_NH -0.370 0.253
10 80.Wht_NH -1.101** 0.197
11 90.Mex_Am -0.564** 0.216
12 90.Oth_H -0.347 0.219
13 90.Oth_NH -0.564* 0.254
14 90.Wht_NH -1.499** 0.199
mgen
15 US native 5.023** 0.180
year.mgen
16 80.US native -0.943** 0.186
17 90.US native -1.507** 0.187
meth.mgen
18 Mex_Am.US native -2.946** 0.203
19 Oth_H.US native -2.563** 0.206
20 Oth_NH.US native -2.763** 0.245
21 Wht_NH.US native -0.794** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.426* 0.210
23 80.Oth_H.US native -0.860** 0.214
24 80.Oth_NH.US native 0.264 0.253
25 80.Wht_NH.US native 0.715** 0.190
26 90.Mex_Am.US native 0.620** 0.211
27 90.Oth_H.US native -0.382 0.215
28 90.Oth_NH.US native 0.650* 0.254
29 90.Wht_NH.US native 1.175** 0.191
feth
30 Mex_Am 4.616** 0.288
31 Oth_H 4.541** 0.292
32 Oth_NH 5.267** 0.288
33 Wht_NH 5.487** 0.275
year.feth
34 80.Mex_Am -0.795** 0.295
35 80.Oth_H -0.030 0.298
36 80.Oth_NH -0.383 0.294
37 80.Wht_NH -1.262** 0.280
38 90.Mex_Am -0.592* 0.296
39 90.Oth_H 0.093 0.300
40 90.Oth_NH -0.413 0.295
41 90.Wht_NH -1.454** 0.282
fgen
42 US native 5.806** 0.268
year.fgen
43 80.US native -1.536** 0.273
44 90.US native -2.016** 0.274
feth.fgen
45 Mex_Am.US native -3.691** 0.285
46 Oth_H.US native -3.191** 0.288
47 Oth_NH.US native -4.576** 0.287
48 Wht_NH.US native -1.906** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.526** 0.291
50 80.Oth_H.US native -0.108 0.295
51 80.Oth_NH.US native 1.069** 0.294
52 80.Wht_NH.US native 1.605** 0.275
53 90.Mex_Am.US native 1.715** 0.292
54 90.Oth_H.US native 0.175 0.296
55 90.Oth_NH.US native 1.490** 0.295
56 90.Wht_NH.US native 2.045** 0.277
ethintct
57 1 6.866** 0.037
58 2 3.261** 0.023
59 3 2.630** 0.026
60 4 2.134** 0.029
61 5 2.488** 0.019
62 _cons -9.283** 0.324
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 5070.055
Prob > chi2(163) = 0.0000
. predict P6
(option n assumed; predicted number of events)
. gen ID6=50*(abs((P6/649821)-(count/649821)))
. table year, contents(sum ID6) row
----------------------
year | sum(ID6)
----------+-----------
70 | .2098834
80 | .438056
90 | .3705319
|
Total | 1.018471
----------------------
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -2607.174
LR chi square: 4500012.948
Model degrees of freedom: 71
Pseudo R-squared: 0.999
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.774** 0.371
2 90 5.873** 0.372
meth
3 Mex_Am 3.845** 0.224
4 Oth_H 3.720** 0.226
5 Oth_NH 3.126** 0.261
6 Wht_NH 4.021** 0.215
year.meth
7 80.Mex_Am -0.619** 0.232
8 80.Oth_H -0.040 0.234
9 80.Oth_NH -0.369 0.270
10 80.Wht_NH -1.032** 0.223
11 90.Mex_Am -0.812** 0.232
12 90.Oth_H -0.586* 0.235
13 90.Oth_NH -0.722** 0.271
14 90.Wht_NH -1.448** 0.224
mgen
15 US native 5.023** 0.180
year.mgen
16 80.US native -0.944** 0.186
17 90.US native -1.508** 0.187
meth.mgen
18 Mex_Am.US native -2.957** 0.203
19 Oth_H.US native -2.570** 0.206
20 Oth_NH.US native -2.833** 0.245
21 Wht_NH.US native -0.794** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.436* 0.210
23 80.Oth_H.US native -0.849** 0.214
24 80.Oth_NH.US native 0.328 0.254
25 80.Wht_NH.US native 0.714** 0.190
26 90.Mex_Am.US native 0.638** 0.211
27 90.Oth_H.US native -0.360 0.215
28 90.Oth_NH.US native 0.743** 0.254
29 90.Wht_NH.US native 1.175** 0.191
feth
30 Mex_Am 5.093** 0.312
31 Oth_H 4.962** 0.314
32 Oth_NH 5.733** 0.311
33 Wht_NH 5.747** 0.303
year.feth
34 80.Mex_Am -1.129** 0.321
35 80.Oth_H -0.199 0.323
36 80.Oth_NH -0.641* 0.319
37 80.Wht_NH -1.356** 0.312
38 90.Mex_Am -1.435** 0.322
39 90.Oth_H -0.775* 0.324
40 90.Oth_NH -1.314** 0.320
41 90.Wht_NH -2.035** 0.313
fgen
42 US native 5.806** 0.268
year.fgen
43 80.US native -1.536** 0.273
44 90.US native -2.017** 0.274
feth.fgen
45 Mex_Am.US native -3.705** 0.285
46 Oth_H.US native -3.202** 0.288
47 Oth_NH.US native -4.599** 0.287
48 Wht_NH.US native -1.906** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.535** 0.291
50 80.Oth_H.US native -0.091 0.295
51 80.Oth_NH.US native 1.088** 0.294
52 80.Wht_NH.US native 1.604** 0.275
53 90.Mex_Am.US native 1.739** 0.292
54 90.Oth_H.US native 0.202 0.297
55 90.Oth_NH.US native 1.525** 0.295
56 90.Wht_NH.US native 2.045** 0.277
ethintct
57 1 7.733** 0.161
58 2 3.625** 0.107
59 3 3.203** 0.101
60 4 3.186** 0.128
61 5 3.136** 0.088
ethintct.year
62 1.80 -0.616** 0.170
63 1.90 -1.393** 0.170
64 2.80 -0.232* 0.112
65 2.90 -0.529** 0.112
66 3.80 -0.723** 0.108
67 3.90 -0.597** 0.109
68 4.80 -1.029** 0.134
69 4.90 -1.185** 0.135
70 5.80 -0.583** 0.092
71 5.90 -0.839** 0.093
72 _cons -10.131** 0.360
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 3882.347
Prob > chi2(153) = 0.0000
. predict P7
(option n assumed; predicted number of events)
. gen ID7=50*(abs((P7/649821)-(count/649821)))
. table year, contents(sum ID7) row
----------------------
year | sum(ID7)
----------+-----------
70 | .0724216
80 | .3765209
90 | .2951791
|
Total | .7441217
----------------------
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year BW MOh
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -2267.900
LR chi square: 4500691.495
Model degrees of freedom: 73
Pseudo R-squared: 0.999
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.768** 0.369
2 90 5.859** 0.370
meth
3 Mex_Am 2.925** 0.227
4 Oth_H 2.805** 0.230
5 Oth_NH 2.270** 0.264
6 Wht_NH 3.630** 0.213
year.meth
7 80.Mex_Am -0.595* 0.232
8 80.Oth_H -0.026 0.235
9 80.Oth_NH -0.368 0.270
10 80.Wht_NH -1.045** 0.221
11 90.Mex_Am -0.784** 0.233
12 90.Oth_H -0.569* 0.236
13 90.Oth_NH -0.713** 0.271
14 90.Wht_NH -1.450** 0.222
mgen
15 US native 5.023** 0.180
year.mgen
16 80.US native -0.945** 0.186
17 90.US native -1.511** 0.187
meth.mgen
18 Mex_Am.US native -2.956** 0.203
19 Oth_H.US native -2.569** 0.206
20 Oth_NH.US native -2.830** 0.245
21 Wht_NH.US native -0.794** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.438* 0.210
23 80.Oth_H.US native -0.843** 0.214
24 80.Oth_NH.US native 0.335 0.254
25 80.Wht_NH.US native 0.716** 0.190
26 90.Mex_Am.US native 0.642** 0.211
27 90.Oth_H.US native -0.353 0.215
28 90.Oth_NH.US native 0.754** 0.254
29 90.Wht_NH.US native 1.178** 0.191
feth
30 Mex_Am 4.156** 0.314
31 Oth_H 4.028** 0.317
32 Oth_NH 4.869** 0.313
33 Wht_NH 5.355** 0.302
year.feth
34 80.Mex_Am -1.110** 0.321
35 80.Oth_H -0.187 0.324
36 80.Oth_NH -0.643* 0.320
37 80.Wht_NH -1.362** 0.311
38 90.Mex_Am -1.414** 0.322
39 90.Oth_H -0.763* 0.325
40 90.Oth_NH -1.319** 0.321
41 90.Wht_NH -2.039** 0.312
fgen
42 US native 5.806** 0.268
year.fgen
43 80.US native -1.537** 0.273
44 90.US native -2.018** 0.274
feth.fgen
45 Mex_Am.US native -3.704** 0.285
46 Oth_H.US native -3.201** 0.288
47 Oth_NH.US native -4.596** 0.287
48 Wht_NH.US native -1.906** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.536** 0.291
50 80.Oth_H.US native -0.090 0.295
51 80.Oth_NH.US native 1.097** 0.294
52 80.Wht_NH.US native 1.605** 0.275
53 90.Mex_Am.US native 1.740** 0.292
54 90.Oth_H.US native 0.204 0.297
55 90.Oth_NH.US native 1.536** 0.295
56 90.Wht_NH.US native 2.046** 0.277
ethintct
57 1 6.418** 0.164
58 2 4.164** 0.111
59 3 3.734** 0.105
60 4 3.586** 0.134
61 5 2.604** 0.093
ethintct.year
62 1.80 -0.608** 0.165
63 1.90 -1.375** 0.165
64 2.80 -0.269* 0.112
65 2.90 -0.564** 0.113
66 3.80 -0.746** 0.109
67 3.90 -0.614** 0.110
68 4.80 -1.032** 0.139
69 4.90 -1.187** 0.140
70 5.80 -0.558** 0.094
71 5.90 -0.819** 0.094
BW
72 1 -1.090** 0.043
MOh
73 1 0.645** 0.042
74 _cons -8.816** 0.361
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 3203.8
Prob > chi2(151) = 0.0000
. predict P8
(option n assumed; predicted number of events)
. gen ID8=50*(abs((P8/649821)-(count/649821)))
. table year, contents(sum ID8) row
----------------------
year | sum(ID8)
----------+-----------
70 | .0692804
80 | .3472032
90 | .2713626
|
Total | .6878462
----------------------
. *We've still got a LOT of residual df to work with here.
. *One thing I don't think we can add is mgen*fgen, because we don't have a 2x2
> table which would allow for a single interaction.
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year BW MOh mg
> en*fgen
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -2267.900
LR chi square: 4500691.495
Model degrees of freedom: 73
Pseudo R-squared: 0.999
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.768** 0.369
2 90 5.859** 0.370
meth
3 Mex_Am 2.925** 0.227
4 Oth_H 2.805** 0.230
5 Oth_NH 2.270** 0.264
6 Wht_NH 3.630** 0.213
year.meth
7 80.Mex_Am -0.595* 0.232
8 80.Oth_H -0.026 0.235
9 80.Oth_NH -0.368 0.270
10 80.Wht_NH -1.045** 0.221
11 90.Mex_Am -0.784** 0.233
12 90.Oth_H -0.569* 0.236
13 90.Oth_NH -0.713** 0.271
14 90.Wht_NH -1.450** 0.222
mgen
15 US native 5.023** 0.180
year.mgen
16 80.US native -0.945** 0.186
17 90.US native -1.511** 0.187
meth.mgen
18 Mex_Am.US native -2.956** 0.203
19 Oth_H.US native -2.569** 0.206
20 Oth_NH.US native -2.830** 0.245
21 Wht_NH.US native -0.794** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.438* 0.210
23 80.Oth_H.US native -0.843** 0.214
24 80.Oth_NH.US native 0.335 0.254
25 80.Wht_NH.US native 0.716** 0.190
26 90.Mex_Am.US native 0.642** 0.211
27 90.Oth_H.US native -0.353 0.215
28 90.Oth_NH.US native 0.754** 0.254
29 90.Wht_NH.US native 1.178** 0.191
feth
30 Mex_Am 4.156** 0.314
31 Oth_H 4.028** 0.317
32 Oth_NH 4.869** 0.313
33 Wht_NH 5.355** 0.302
year.feth
34 80.Mex_Am -1.110** 0.321
35 80.Oth_H -0.187 0.324
36 80.Oth_NH -0.643* 0.320
37 80.Wht_NH -1.362** 0.311
38 90.Mex_Am -1.414** 0.322
39 90.Oth_H -0.763* 0.325
40 90.Oth_NH -1.319** 0.321
41 90.Wht_NH -2.039** 0.312
fgen
42 US native 5.806** 0.268
year.fgen
43 80.US native -1.537** 0.273
44 90.US native -2.018** 0.274
feth.fgen
45 Mex_Am.US native -3.704** 0.285
46 Oth_H.US native -3.201** 0.288
47 Oth_NH.US native -4.596** 0.287
48 Wht_NH.US native -1.906** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.536** 0.291
50 80.Oth_H.US native -0.090 0.295
51 80.Oth_NH.US native 1.097** 0.294
52 80.Wht_NH.US native 1.605** 0.275
53 90.Mex_Am.US native 1.740** 0.292
54 90.Oth_H.US native 0.204 0.297
55 90.Oth_NH.US native 1.536** 0.295
56 90.Wht_NH.US native 2.046** 0.277
ethintct
57 1 6.418** 0.164
58 2 4.164** 0.111
59 3 3.734** 0.105
60 4 3.586** 0.134
61 5 2.604** 0.093
ethintct.year
62 1.80 -0.608** 0.165
63 1.90 -1.375** 0.165
64 2.80 -0.269* 0.112
65 2.90 -0.564** 0.113
66 3.80 -0.746** 0.109
67 3.90 -0.614** 0.110
68 4.80 -1.032** 0.139
69 4.90 -1.187** 0.140
70 5.80 -0.558** 0.094
71 5.90 -0.819** 0.094
BW
72 1 -1.090** 0.043
MOh
73 1 0.645** 0.042
74 _cons -8.816** 0.361
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 3203.8
Prob > chi2(151) = 0.0000
. *Right. It's the same.
.
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year BW MOh meth*fgen feth*mgen
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -1692.884
LR chi square: 4501841.527
Model degrees of freedom: 81
Pseudo R-squared: 0.999
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 4.746** 0.369
2 90 5.853** 0.371
meth
3 Mex_Am 2.627** 0.248
4 Oth_H 2.460** 0.251
5 Oth_NH 0.923** 0.283
6 Wht_NH 3.434** 0.233
year.meth
7 80.Mex_Am -0.573* 0.233
8 80.Oth_H -0.021 0.235
9 80.Oth_NH -0.450 0.269
10 80.Wht_NH -1.014** 0.221
11 90.Mex_Am -0.741** 0.234
12 90.Oth_H -0.575* 0.236
13 90.Oth_NH -0.815** 0.270
14 90.Wht_NH -1.427** 0.222
mgen
15 US native 5.018** 0.180
year.mgen
16 80.US native -0.952** 0.186
17 90.US native -1.525** 0.187
meth.mgen
18 Mex_Am.US native -2.851** 0.220
19 Oth_H.US native -2.698** 0.223
20 Oth_NH.US native -3.141** 0.259
21 Wht_NH.US native -0.973** 0.201
year.meth.mgen
22 80.Mex_Am.US native 0.438* 0.210
23 80.Oth_H.US native -0.829** 0.214
24 80.Oth_NH.US native 0.440 0.254
25 80.Wht_NH.US native 0.723** 0.190
26 90.Mex_Am.US native 0.634** 0.211
27 90.Oth_H.US native -0.323 0.215
28 90.Oth_NH.US native 0.886** 0.255
29 90.Wht_NH.US native 1.194** 0.191
feth
30 Mex_Am 4.964** 0.331
31 Oth_H 4.670** 0.333
32 Oth_NH 5.272** 0.329
33 Wht_NH 5.694** 0.318
year.feth
34 80.Mex_Am -1.120** 0.322
35 80.Oth_H -0.273 0.324
36 80.Oth_NH -0.829** 0.318
37 80.Wht_NH -1.340** 0.311
38 90.Mex_Am -1.425** 0.323
39 90.Oth_H -0.860** 0.325
40 90.Oth_NH -1.538** 0.319
41 90.Wht_NH -2.026** 0.312
fgen
42 US native 5.800** 0.268
year.fgen
43 80.US native -1.539** 0.273
44 90.US native -2.030** 0.274
feth.fgen
45 Mex_Am.US native -4.146** 0.290
46 Oth_H.US native -3.812** 0.294
47 Oth_NH.US native -5.600** 0.293
48 Wht_NH.US native -2.368** 0.275
year.feth.fgen
49 80.Mex_Am.US native 1.531** 0.291
50 80.Oth_H.US native -0.019 0.295
51 80.Oth_NH.US native 1.323** 0.295
52 80.Wht_NH.US native 1.606** 0.275
53 90.Mex_Am.US native 1.734** 0.292
54 90.Oth_H.US native 0.282 0.297
55 90.Oth_NH.US native 1.807** 0.297
56 90.Wht_NH.US native 2.056** 0.277
ethintct
57 1 6.679** 0.167
58 2 4.017** 0.111
59 3 3.628** 0.106
60 4 3.799** 0.136
61 5 2.712** 0.093
ethintct.year
62 1.80 -0.578** 0.166
63 1.90 -1.344** 0.166
64 2.80 -0.253* 0.112
65 2.90 -0.568** 0.113
66 3.80 -0.697** 0.110
67 3.90 -0.559** 0.111
68 4.80 -0.965** 0.141
69 4.90 -1.122** 0.142
70 5.80 -0.589** 0.094
71 5.90 -0.849** 0.094
BW
72 1 -0.900** 0.046
MOh
73 1 0.496** 0.042
meth.fgen
74 Mex_Am.US native 0.421** 0.061
75 Oth_H.US native 0.685** 0.065
76 Oth_NH.US native 1.847** 0.074
77 Wht_NH.US native 0.466** 0.054
feth.mgen
78 Mex_Am.US native -0.197* 0.087
79 Oth_H.US native 0.132 0.090
80 Oth_NH.US native 0.610** 0.098
81 Wht_NH.US native 0.184* 0.084
82 _cons -9.066** 0.363
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 2053.768
Prob > chi2(143) = 0.0000
. display 2053-143*(ln(649821))
139.02333
. predict P9a
(option n assumed; predicted number of events)
. gen ID9a=50*(abs((P9a/649821)-(count/649821)))
. table year, contents(sum ID9a) row
----------------------
year | sum(ID9a)
----------+-----------
70 | .0618134
80 | .2328922
90 | .171231
|
Total | .4659366
----------------------
. desmat: poisson count year*meth*mgen*fgen year*feth*fgen*mgen ethintct*year* mgen*fgen BW MOh
Hessian has become unstable or asymmetric (NC)
--Break--
r(1);
. desmat: poisson count year*meth*mgen*fgen year*feth*fgen*mgen ethintct*year*mgen*fgen BW MOh, difficult
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -934.270
LR chi square: 4503358.755
Model degrees of freedom: 127
Pseudo R-squared: 1.000
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 2.940** 0.783
2 90 3.633** 0.766
meth
3 Mex_Am 0.416 0.576
4 Oth_H 1.542** 0.547
5 Oth_NH 0.757 0.456
6 Wht_NH 2.370** 0.553
year.meth
7 80.Mex_Am -0.236 0.365
8 80.Oth_H 0.283 0.449
9 80.Oth_NH 0.621 0.476
10 90.Mex_Am 0.221 0.454
11 90.Oth_H -0.168 0.572
12 90.Oth_NH 0.723 0.724
13 90.Wht_NH -0.709 0.492
mgen
14 US native 2.275** 0.562
meth.mgen
15 Mex_Am.US native -1.018* 0.453
16 Oth_H.US native -1.490** 0.444
17 Oth_NH.US native -2.187** 0.687
18 Wht_NH.US native 0.396 0.489
year.meth.mgen
19 80.Oth_H.US native -1.549** 0.562
20 80.Oth_NH.US native -0.732 0.714
21 80.Wht_NH.US native -0.566* 0.267
22 90.Mex_Am.US native -0.255 0.585
23 90.Oth_H.US native -0.679 0.462
24 90.Oth_NH.US native -0.371 0.491
25 90.Wht_NH.US native 0.295 0.560
fgen
26 US native 3.069** 0.770
meth.fgen
27 Mex_Am.US native 0.805* 0.373
28 Oth_H.US native 0.279 0.340
29 Wht_NH.US native 0.145 0.289
year.meth.fgen
30 80.Mex_Am.US native 0.516 0.586
31 80.Wht_NH.US native -0.260 0.495
32 90.Oth_H.US native 0.031 0.360
33 90.Oth_NH.US native -0.333 0.550
year.mgen.fgen
34 80.US native.US native -0.083 0.588
35 90.US native.US native -0.242 0.586
meth.mgen.fgen
36 Oth_NH.US native.US native 1.068* 0.531
year.meth.mgen.fgen
37 80.Mex_Am.US native.US native -0.380 0.475
38 80.Oth_H.US native.US native 0.525 0.359
39 80.Oth_NH.US native.US native 0.092 0.550
40 80.Wht_NH.US native.US native 0.600 0.578
41 90.Mex_Am.US native.US native -0.070 0.388
42 90.Wht_NH.US native.US native 0.255 0.300
feth
43 Mex_Am 1.740* 0.851
44 Oth_H 2.764** 0.835
45 Oth_NH 3.144** 0.716
46 Wht_NH 3.402** 0.840
year.feth
47 80.Mex_Am 0.577 0.437
48 80.Oth_H -0.587 0.876
49 80.Oth_NH 0.191 0.930
50 80.Wht_NH -0.245 0.780
51 90.Mex_Am -0.843 0.874
52 90.Oth_H -0.977 0.859
53 90.Oth_NH -0.612 0.916
54 90.Wht_NH -1.520* 0.763
year.fgen
55 80.US native -0.709 0.962
56 90.US native -1.197 0.946
feth.fgen
57 Mex_Am.US native -1.612* 0.739
58 Oth_H.US native -2.029** 0.732
59 Oth_NH.US native -3.717** 0.878
60 Wht_NH.US native -0.494 0.761
year.feth.fgen
61 80.Oth_H.US native 0.013 0.767
62 80.Oth_NH.US native 0.408 0.766
63 80.Wht_NH.US native 0.297 0.863
64 90.Mex_Am.US native 1.518* 0.756
65 90.Oth_H.US native 0.655 0.748
66 90.Oth_NH.US native 1.219 0.748
67 90.Wht_NH.US native 1.569 0.848
feth.mgen
68 Mex_Am.US native 0.511 0.447
69 Oth_H.US native 0.144 0.428
70 Wht_NH.US native 0.634 0.387
year.feth.mgen
71 80.Mex_Am.US native -1.079 0.875
72 80.Oth_H.US native 0.489 0.452
73 80.Oth_NH.US native -0.008 0.553
74 90.Mex_Am.US native -0.243 0.466
75 90.Oth_H.US native -0.045 0.451
76 90.Oth_NH.US native -0.219 0.555
feth.fgen.mgen
77 Oth_NH.US native.US native 0.845 0.533
year.feth.fgen.mgen
78 80.Mex_Am.US native.US native 1.029 0.775
79 80.Wht_NH.US native.US native 0.330 0.405
80 90.Wht_NH.US native.US native 0.139 0.406
ethintct
81 1 3.893** 0.805
82 2 3.672** 0.500
83 3 -1.497** 0.536
84 4 2.402** 0.552
85 5 1.594** 0.273
ethintct.year
86 1.80 1.334 1.043
87 1.90 0.651 1.030
88 2.80 -0.161 0.349
89 2.90 -0.365 0.349
90 3.80 3.794** 0.562
91 3.90 1.928** 0.416
92 4.80 -1.206* 0.542
93 4.90 -0.944 0.807
94 5.80 -0.059 0.431
95 5.90 -0.197 0.306
ethintct.mgen
96 2.US native 0.417 0.360
97 3.US native 2.429** 0.357
ethintct.year.mgen
98 1.80.US native -0.962 0.624
99 1.90.US native -1.332* 0.622
100 2.80.US native 0.451 0.502
101 2.90.US native 0.298 0.502
102 3.80.US native -1.861** 0.376
103 4.80.US native 0.485 0.790
104 4.90.US native 0.144 0.568
105 5.80.US native -0.509 0.324
106 5.90.US native -0.294 0.420
ethintct.fgen
107 1.US native -0.060 0.985
108 2.US native 0.035 0.367
109 3.US native 3.109** 0.417
110 4.US native 0.667 0.761
111 5.US native 0.248 0.398
ethintct.year.fgen
112 1.80.US native -0.840 0.857
113 1.90.US native -0.554 0.842
114 3.80.US native -2.846** 0.437
115 3.90.US native -1.020 0.545
116 4.90.US native -0.316 0.596
117 5.80.US native -0.092 0.306
ethintct.mgen.fgen
118 1.US native.US native 2.939** 0.596
119 4.US native.US native 0.909 0.546
120 5.US native.US native 0.948** 0.310
ethintct.year.mgen.fgen
121 2.80.US native.US native -0.624 0.383
122 2.90.US native.US native -0.563 0.384
123 3.90.US native.US native -1.745** 0.375
124 4.80.US native.US native -0.215 0.597
125 5.90.US native.US native -0.487 0.309
BW
126 1 -0.920** 0.047
MOh
127 1 0.530** 0.044
128 _cons -3.683** 0.937
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 536.5403
Prob > chi2(97) = 0.0000
. display 536.5-97*(ln(649821))
-761.79187
. predict P9b
(option n assumed; predicted number of events)
. gen ID9b=50*(abs((P9b/649821)-(count/649821)))
. table year, contents(sum ID9b) row
----------------------
year | sum(ID9b)
----------+-----------
70 | .0110661
80 | .0610986
90 | .0604668
|
Total | .1326315
----------------------
. table meth feth, contents (mean QS)
--------------------------------------------------
| feth
meth | Blk_NH Mex_Am Oth_H Oth_NH Wht_NH
----------+---------------------------------------
Blk_NH | 0 3 0 0 1
Mex_Am | 3 0 2 0 0
Oth_H | 0 2 0 5 0
Oth_NH | 0 0 5 0 4
Wht_NH | 1 0 0 4 0
--------------------------------------------------
. *so This is not a full set of QS terms; we're leaving some out so that we can
> keep the ethnic endogamy diagonal terms as well
. desmat: poisson count year*meth*mgen*fgen year*feth*fgen*mgen ethintct*year*mgen*fgen QS*year QS*mgen QS*fgen BOhS*fgen BWS*year, difficult
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -719.657
LR chi square: 4503787.980
Model degrees of freedom: 155
Pseudo R-squared: 1.000
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 3.287** 0.856
2 90 3.770** 0.840
meth
3 Mex_Am 0.434 0.674
4 Oth_H 1.763** 0.672
5 Oth_NH 0.013 0.552
6 Wht_NH 0.977 0.658
year.meth
7 80.Mex_Am -0.235 0.454
8 80.Oth_H 0.303 0.576
9 80.Oth_NH 1.052 0.550
10 90.Mex_Am 0.489 0.576
11 90.Oth_H -0.176 0.656
12 90.Oth_NH 0.924 0.772
13 90.Wht_NH -0.281 0.524
mgen
14 US native 2.807** 0.610
meth.mgen
15 Mex_Am.US native -1.128* 0.496
16 Oth_H.US native -1.639** 0.492
17 Oth_NH.US native -3.125** 0.776
18 Wht_NH.US native -0.049 0.500
year.meth.mgen
19 80.Oth_H.US native -1.561** 0.573
20 80.Oth_NH.US native -0.719 0.725
21 80.Wht_NH.US native -0.160 0.312
22 90.Mex_Am.US native -0.377 0.591
23 90.Oth_H.US native -0.658 0.465
24 90.Oth_NH.US native -0.320 0.494
25 90.Wht_NH.US native 0.127 0.576
fgen
26 US native 2.919** 0.815
meth.fgen
27 Mex_Am.US native 1.029* 0.404
28 Oth_H.US native 0.290 0.382
29 Wht_NH.US native 0.547 0.427
year.meth.fgen
30 80.Mex_Am.US native 0.523 0.592
31 80.Wht_NH.US native 0.211 0.527
32 90.Oth_H.US native 0.307 0.377
33 90.Oth_NH.US native -0.147 0.561
year.mgen.fgen
34 80.US native.US native 0.126 0.600
35 90.US native.US native -0.172 0.598
meth.mgen.fgen
36 Oth_NH.US native.US native 1.358* 0.629
year.meth.mgen.fgen
37 80.Mex_Am.US native.US native -0.381 0.474
38 80.Oth_H.US native.US native 0.541 0.374
39 80.Oth_NH.US native.US native 0.119 0.561
40 80.Wht_NH.US native.US native 0.186 0.605
41 90.Mex_Am.US native.US native 0.069 0.400
42 90.Wht_NH.US native.US native 0.434 0.317
feth
43 Mex_Am 2.632** 0.959
44 Oth_H 3.799** 0.955
45 Oth_NH 2.278** 0.800
46 Wht_NH 2.854** 0.870
year.feth
47 80.Mex_Am 0.144 0.563
48 80.Oth_H -1.074 0.960
49 80.Oth_NH 0.114 0.963
50 80.Wht_NH -0.635 0.803
51 90.Mex_Am -1.099 0.950
52 90.Oth_H -1.257 0.946
53 90.Oth_NH -0.805 0.949
54 90.Wht_NH -1.842* 0.786
year.fgen
55 80.US native -1.093 0.976
56 90.US native -1.539 0.961
feth.fgen
57 Mex_Am.US native -1.799* 0.765
58 Oth_H.US native -2.284** 0.761
59 Oth_NH.US native -2.939** 0.921
60 Wht_NH.US native -0.383 0.783
year.feth.fgen
61 80.Oth_H.US native 0.138 0.771
62 80.Oth_NH.US native 0.534 0.771
63 80.Wht_NH.US native 0.716 0.870
64 90.Mex_Am.US native 1.572* 0.758
65 90.Oth_H.US native 0.758 0.753
66 90.Oth_NH.US native 1.310 0.752
67 90.Wht_NH.US native 1.829* 0.855
feth.mgen
68 Mex_Am.US native 0.570 0.495
69 Oth_H.US native 0.053 0.485
70 Wht_NH.US native 0.259 0.405
year.feth.mgen
71 80.Mex_Am.US native -1.370 0.881
72 80.Oth_H.US native 0.246 0.470
73 80.Oth_NH.US native -0.234 0.570
74 90.Mex_Am.US native -0.365 0.478
75 90.Oth_H.US native -0.153 0.469
76 90.Oth_NH.US native -0.266 0.572
feth.fgen.mgen
77 Oth_NH.US native.US native 0.156 0.560
year.feth.fgen.mgen
78 80.Mex_Am.US native.US native 1.103 0.777
79 80.Wht_NH.US native.US native 0.103 0.420
80 90.Wht_NH.US native.US native 0.032 0.421
ethintct
81 1 3.031** 0.897
82 2 2.433** 0.729
83 3 0.421 0.537
84 5 3.492** 0.573
ethintct.year
85 1.80 1.195 1.089
86 1.90 -0.817 0.891
87 2.90 0.028 0.518
88 3.80 2.309** 0.575
89 3.90 3.894** 0.696
90 4.80 -1.211 0.686
91 4.90 -0.948 0.686
92 5.80 -0.614 0.489
93 5.90 0.190 0.598
ethintct.mgen
94 2.US native -0.064 0.426
95 3.US native -1.366* 0.645
96 4.US native 4.088** 0.735
ethintct.year.mgen
97 1.80.US native -1.171 0.635
98 2.80.US native 0.667 0.515
99 3.90.US native -1.729** 0.380
100 5.80.US native -0.319 0.427
101 5.90.US native -0.755* 0.331
ethintct.fgen
102 1.US native 0.622 1.043
103 2.US native 0.149 0.493
104 4.US native 3.722** 0.665
105 5.US native -0.402 0.552
ethintct.year.fgen
106 1.80.US native -0.665 0.863
107 1.90.US native 1.120 1.027
108 2.80.US native 0.301 0.513
109 2.90.US native -0.253 0.496
110 3.80.US native -0.982 0.554
111 3.90.US native -2.872** 0.442
112 4.80.US native -0.438 0.809
113 4.90.US native -0.392 0.809
114 5.90.US native -0.547 0.315
ethintct.mgen.fgen
115 1.US native.US native 2.407** 0.642
116 3.US native.US native 3.504** 0.536
117 4.US native.US native -2.374* 0.944
118 5.US native.US native 1.235** 0.384
ethintct.year.mgen.fgen
119 1.90.US native.US native -1.402* 0.634
120 2.80.US native.US native -0.828 0.643
121 2.90.US native.US native -0.230 0.376
122 3.80.US native.US native -1.830** 0.381
123 4.80.US native.US native 0.246 0.582
124 4.90.US native.US native 0.070 0.584
125 5.80.US native.US native -0.166 0.312
QS
126 BW 0.165 0.515
127 Moh -0.209 0.559
128 BM -3.206** 0.596
129 WO 1.447** 0.485
130 OOh -1.823** 0.398
QS.year
131 BW.80 -0.743 0.455
132 BW.90 -0.345 0.456
133 Moh.80 0.376 0.405
134 Moh.90 0.055 0.408
135 BM.80 1.189** 0.447
136 BM.90 1.260** 0.447
137 WO.80 -0.482 0.324
138 WO.90 -0.173 0.328
139 OOh.80 0.353 0.336
140 OOh.90 0.589 0.336
QS.mgen
141 BW.US native -0.281 0.227
142 Moh.US native -0.669** 0.235
143 BM.US native 0.082 0.228
144 WO.US native 0.431* 0.213
145 OOh.US native 1.031** 0.168
QS.fgen
146 BW.US native -0.132 0.175
147 Moh.US native -0.223 0.342
148 BM.US native 0.667 0.346
149 WO.US native -0.357 0.321
150 OOh.US native 0.439* 0.175
BOhS
151 1 -1.556** 0.319
BOhS.fgen
152 1.US native 0.866** 0.324
BWS
153 1 -0.666 0.345
BWS.year
154 1.80 0.874* 0.351
155 1.90 0.771* 0.351
156 _cons -3.353** 1.033
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 107.3149
Prob > chi2(69) = 0.0022
. display 107.3-69*(ln(649821))
-816.2272
. predict P9c
(option n assumed; predicted number of events)
. gen ID9c=50*(abs((P9c/649821)-(count/649821)))
. table year, contents(sum ID9c) row
----------------------
year | sum(ID9c)
----------+-----------
70 | .0061056
80 | .0232677
90 | .0220148
|
Total | .0513881
----------------------
. desmat: poisson count year*meth*mgen*fgen year*feth*fgen*mgen ethintct*year* mgen*fgen QS*year*mgen*fgen BOhS*fgen BWS*year, difficult
Hessian has become unstable or asymmetric (D)
--Break--
r(1);
. desmat: poisson count year*meth*mgen*fgen year*feth*fgen*mgen ethintct*year*mgen*fgen QS*mgen*fgen QS*year BOhS*fgen BWS*year, difficult
-------------------------------------------------------------------------------
Poisson regression
-------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -719.657
LR chi square: 4503787.980
Model degrees of freedom: 155
Pseudo R-squared: 1.000
Prob: 0.000
-------------------------------------------------------------------------------
nr Effect Coeff s.e.
-------------------------------------------------------------------------------
count
year
1 80 3.287** 0.856
2 90 3.770** 0.840
meth
3 Mex_Am 0.434 0.674
4 Oth_H 1.763** 0.672
5 Oth_NH 0.013 0.552
6 Wht_NH 0.977 0.658
year.meth
7 80.Mex_Am -0.235 0.454
8 80.Oth_H 0.303 0.576
9 80.Oth_NH 1.052 0.550
10 90.Mex_Am 0.489 0.576
11 90.Oth_H -0.176 0.656
12 90.Oth_NH 0.924 0.772
13 90.Wht_NH -0.281 0.524
mgen
14 US native 2.807** 0.610
meth.mgen
15 Mex_Am.US native -1.128* 0.496
16 Oth_H.US native -1.639** 0.492
17 Oth_NH.US native -3.125** 0.776
18 Wht_NH.US native -0.049 0.500
year.meth.mgen
19 80.Oth_H.US native -1.561** 0.573
20 80.Oth_NH.US native -0.719 0.725
21 80.Wht_NH.US native -0.160 0.312
22 90.Mex_Am.US native -0.377 0.591
23 90.Oth_H.US native -0.658 0.465
24 90.Oth_NH.US native -0.320 0.494
25 90.Wht_NH.US native 0.127 0.576
fgen
26 US native 2.919** 0.815
meth.fgen
27 Mex_Am.US native 1.029* 0.404
28 Oth_H.US native 0.290 0.382
29 Wht_NH.US native 0.547 0.427
year.meth.fgen
30 80.Mex_Am.US native 0.523 0.592
31 80.Wht_NH.US native 0.211 0.527
32 90.Oth_H.US native 0.307 0.377
33 90.Oth_NH.US native -0.147 0.561
year.mgen.fgen
34 80.US native.US native 0.126 0.600
35 90.US native.US native -0.172 0.598
meth.mgen.fgen
36 Oth_NH.US native.US native 1.358* 0.629
year.meth.mgen.fgen
37 80.Mex_Am.US native.US native -0.381 0.474
38 80.Oth_H.US native.US native 0.541 0.374
39 80.Oth_NH.US native.US native 0.119 0.561
40 80.Wht_NH.US native.US native 0.186 0.605
41 90.Mex_Am.US native.US native 0.069 0.400
42 90.Wht_NH.US native.US native 0.434 0.317
feth
43 Mex_Am 2.632** 0.959
44 Oth_H 3.799** 0.955
45 Oth_NH 2.278** 0.800
46 Wht_NH 2.854** 0.870
year.feth
47 80.Mex_Am 0.144 0.563
48 80.Oth_H -1.074 0.960
49 80.Oth_NH 0.114 0.963
50 80.Wht_NH -0.635 0.803
51 90.Mex_Am -1.099 0.950
52 90.Oth_H -1.257 0.946
53 90.Oth_NH -0.805 0.949
54 90.Wht_NH -1.842* 0.786
year.fgen
55 80.US native -1.093 0.976
56 90.US native -1.539 0.961
feth.fgen
57 Mex_Am.US native -1.799* 0.765
58 Oth_H.US native -2.284** 0.761
59 Oth_NH.US native -2.939** 0.921
60 Wht_NH.US native -0.383 0.783
year.feth.fgen
61 80.Oth_H.US native 0.138 0.771
62 80.Oth_NH.US native 0.534 0.771
63 80.Wht_NH.US native 0.716 0.870
64 90.Mex_Am.US native 1.572* 0.758
65 90.Oth_H.US native 0.758 0.753
66 90.Oth_NH.US native 1.310 0.752
67 90.Wht_NH.US native 1.829* 0.855
feth.mgen
68 Mex_Am.US native 0.570 0.495
69 Oth_H.US native 0.053 0.485
70 Wht_NH.US native 0.259 0.405
year.feth.mgen
71 80.Mex_Am.US native -1.370 0.881
72 80.Oth_H.US native 0.246 0.470
73 80.Oth_NH.US native -0.234 0.570
74 90.Mex_Am.US native -0.365 0.478
75 90.Oth_H.US native -0.153 0.469
76 90.Oth_NH.US native -0.266 0.572
feth.fgen.mgen
77 Oth_NH.US native.US native 0.156 0.560
year.feth.fgen.mgen
78 80.Mex_Am.US native.US native 1.103 0.777
79 80.Wht_NH.US native.US native 0.103 0.420
80 90.Wht_NH.US native.US native 0.032 0.421
ethintct
81 1 3.031** 0.897
82 2 2.433** 0.729
83 3 0.421 0.537
84 5 3.492** 0.573
ethintct.year
85 1.80 1.195 1.089
86 1.90 -0.817 0.891
87 2.90 0.028 0.518
88 3.80 1.327* 0.524
89 3.90 3.894** 0.696
90 4.80 -1.649* 0.659
91 4.90 -0.948 0.686
92 5.80 -0.933 0.493
93 5.90 0.190 0.598
ethintct.mgen
94 2.US native -0.064 0.426
95 3.US native -1.366* 0.645
96 4.US native 4.088** 0.735
ethintct.year.mgen
97 1.80.US native -1.171 0.635
98 2.80.US native 0.667 0.515
99 3.80.US native 0.982 0.554
100 3.90.US native -1.729** 0.380
101 4.80.US native 0.438 0.809
102 5.90.US native -0.755* 0.331
ethintct.fgen
103 1.US native 0.622 1.043
104 2.US native 0.149 0.493
105 4.US native 3.722** 0.665
106 5.US native -0.402 0.552
ethintct.year.fgen
107 1.80.US native -0.665 0.863
108 1.90.US native 1.120 1.027
109 2.80.US native 0.301 0.513
110 2.90.US native -0.253 0.496
111 3.90.US native -2.872** 0.442
112 4.90.US native -0.392 0.809
113 5.80.US native 0.319 0.427
114 5.90.US native -0.547 0.315
ethintct.mgen.fgen
115 1.US native.US native 2.407** 0.642
116 3.US native.US native 3.504** 0.536
117 4.US native.US native -2.374* 0.944
118 5.US native.US native 1.235** 0.384
ethintct.year.mgen.fgen
119 1.90.US native.US native -1.402* 0.634
120 2.80.US native.US native -0.828 0.643
121 2.90.US native.US native -0.230 0.376
122 3.80.US native.US native -2.812** 0.442
123 4.80.US native.US native -0.192 0.609
124 4.90.US native.US native 0.070 0.584
125 5.80.US native.US native -0.485 0.330
QS
126 BW 0.165 0.515
127 Moh -0.432 0.438
128 BM -2.539** 0.483
129 WO 1.878** 0.441
130 OOh -1.823** 0.398
QS.mgen
131 BW.US native -0.281 0.227
132 Moh.US native -0.446 0.382
133 BM.US native -0.585 0.394
134 OOh.US native 1.031** 0.168
QS.fgen
135 BW.US native -0.132 0.175
136 WO.US native -0.788* 0.359
137 OOh.US native 0.439* 0.175
QS.mgen.fgen
138 Moh.US native.US native -0.223 0.342
139 BM.US native.US native 0.667 0.346
140 WO.US native.US native 0.431* 0.213
QS.year
141 BW.80 -0.743 0.455
142 BW.90 -0.345 0.456
143 Moh.80 0.376 0.405
144 Moh.90 0.055 0.408
145 BM.80 1.189** 0.447
146 BM.90 1.260** 0.447
147 WO.80 -0.482 0.324
148 WO.90 -0.173 0.328
149 OOh.80 0.353 0.336
150 OOh.90 0.589 0.336
BOhS
151 1 -1.556** 0.319
BOhS.fgen
152 1.US native 0.866** 0.324
BWS
153 1 -0.666 0.345
BWS.year
154 1.80 0.874* 0.351
155 1.90 0.771* 0.351
156 _cons -3.353** 1.033
-------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 107.3149
Prob > chi2(69) = 0.0022
. *This is the same as model 9c, because QS*fgen QS*mgen is the same as QS*mgen*fgen since there is no extra interaction term for mgen*fgen
. *Now back to 7a and 7b
. desmat: poisson count year*meth*mgen year*feth*fgen ethinct*year
variable ethinct not found
r(111);
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year
----------------------------------------------------------------------------------
Poisson regression
----------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -2607.174
LR chi square: 4500012.948
Model degrees of freedom: 71
Pseudo R-squared: 0.999
Prob: 0.000
----------------------------------------------------------------------------------
nr Effect Coeff s.e.
----------------------------------------------------------------------------------
count
year
1 80 4.774** 0.371
2 90 5.873** 0.372
meth
3 Mex_Am 3.845** 0.224
4 Oth_H 3.720** 0.226
5 Oth_NH 3.126** 0.261
6 Wht_NH 4.021** 0.215
year.meth
7 80.Mex_Am -0.619** 0.232
8 80.Oth_H -0.040 0.234
9 80.Oth_NH -0.369 0.270
10 80.Wht_NH -1.032** 0.223
11 90.Mex_Am -0.812** 0.232
12 90.Oth_H -0.586* 0.235
13 90.Oth_NH -0.722** 0.271
14 90.Wht_NH -1.448** 0.224
mgen
15 US native 5.023** 0.180
year.mgen
16 80.US native -0.944** 0.186
17 90.US native -1.508** 0.187
meth.mgen
18 Mex_Am.US native -2.957** 0.203
19 Oth_H.US native -2.570** 0.206
20 Oth_NH.US native -2.833** 0.245
21 Wht_NH.US native -0.794** 0.184
year.meth.mgen
22 80.Mex_Am.US native 0.436* 0.210
23 80.Oth_H.US native -0.849** 0.214
24 80.Oth_NH.US native 0.328 0.254
25 80.Wht_NH.US native 0.714** 0.190
26 90.Mex_Am.US native 0.638** 0.211
27 90.Oth_H.US native -0.360 0.215
28 90.Oth_NH.US native 0.743** 0.254
29 90.Wht_NH.US native 1.175** 0.191
feth
30 Mex_Am 5.093** 0.312
31 Oth_H 4.962** 0.314
32 Oth_NH 5.733** 0.311
33 Wht_NH 5.747** 0.303
year.feth
34 80.Mex_Am -1.129** 0.321
35 80.Oth_H -0.199 0.323
36 80.Oth_NH -0.641* 0.319
37 80.Wht_NH -1.356** 0.312
38 90.Mex_Am -1.435** 0.322
39 90.Oth_H -0.775* 0.324
40 90.Oth_NH -1.314** 0.320
41 90.Wht_NH -2.035** 0.313
fgen
42 US native 5.806** 0.268
year.fgen
43 80.US native -1.536** 0.273
44 90.US native -2.017** 0.274
feth.fgen
45 Mex_Am.US native -3.705** 0.285
46 Oth_H.US native -3.202** 0.288
47 Oth_NH.US native -4.599** 0.287
48 Wht_NH.US native -1.906** 0.269
year.feth.fgen
49 80.Mex_Am.US native 1.535** 0.291
50 80.Oth_H.US native -0.091 0.295
51 80.Oth_NH.US native 1.088** 0.294
52 80.Wht_NH.US native 1.604** 0.275
53 90.Mex_Am.US native 1.739** 0.292
54 90.Oth_H.US native 0.202 0.297
55 90.Oth_NH.US native 1.525** 0.295
56 90.Wht_NH.US native 2.045** 0.277
ethintct
57 1 7.733** 0.161
58 2 3.625** 0.107
59 3 3.203** 0.101
60 4 3.186** 0.128
61 5 3.136** 0.088
ethintct.year
62 1.80 -0.616** 0.170
63 1.90 -1.393** 0.170
64 2.80 -0.232* 0.112
65 2.90 -0.529** 0.112
66 3.80 -0.723** 0.108
67 3.90 -0.597** 0.109
68 4.80 -1.029** 0.134
69 4.90 -1.185** 0.135
70 5.80 -0.583** 0.092
71 5.90 -0.839** 0.093
72 _cons -10.131** 0.360
----------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 3882.347
Prob > chi2(153) = 0.0000
. *That's model 7b
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*@year
----------------------------------------------------------------------------------
Poisson regression
----------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -2700.522
LR chi square: 4499826.251
Model degrees of freedom: 66
Pseudo R-squared: 0.999
Prob: 0.000
----------------------------------------------------------------------------------
nr Effect Coeff s.e.
----------------------------------------------------------------------------------
count
year
1 80 1.919** 0.181
meth
2 Mex_Am 3.877** 0.217
3 Oth_H 3.920** 0.220
4 Oth_NH 3.367** 0.253
5 Wht_NH 4.182** 0.202
year.meth
6 80.Mex_Am -0.658** 0.223
7 80.Oth_H -0.300 0.226
8 80.Oth_NH -0.651* 0.260
9 80.Wht_NH -1.236** 0.206
10 90.Mex_Am -0.842** 0.227
11 90.Oth_H -0.751** 0.230
12 90.Oth_NH -0.943** 0.263
13 90.Wht_NH -1.586** 0.214
mgen
14 US native 5.023** 0.180
year.mgen
15 80.US native -0.944** 0.186
16 90.US native -1.508** 0.187
meth.mgen
17 Mex_Am.US native -2.956** 0.203
18 Oth_H.US native -2.568** 0.206
19 Oth_NH.US native -2.801** 0.245
20 Wht_NH.US native -0.794** 0.184
year.meth.mgen
21 80.Mex_Am.US native 0.434* 0.210
22 80.Oth_H.US native -0.863** 0.214
23 80.Oth_NH.US native 0.285 0.253
24 80.Wht_NH.US native 0.715** 0.190
25 90.Mex_Am.US native 0.636** 0.211
26 90.Oth_H.US native -0.354 0.215
27 90.Oth_NH.US native 0.717** 0.254
28 90.Wht_NH.US native 1.175** 0.191
feth
29 Mex_Am 5.107** 0.299
30 Oth_H 5.136** 0.302
31 Oth_NH 5.884** 0.298
32 Wht_NH 5.881** 0.287
year.feth
33 80.Mex_Am -1.140** 0.302
34 80.Oth_H -0.422 0.305
35 80.Oth_NH -0.812** 0.300
36 80.Wht_NH -1.522** 0.287
37 90.Mex_Am -1.450** 0.312
38 90.Oth_H -0.922** 0.315
39 90.Oth_NH -1.452** 0.310
40 90.Wht_NH -2.150** 0.300
fgen
41 US native 5.806** 0.268
year.fgen
42 80.US native -1.536** 0.273
43 90.US native -2.017** 0.274
feth.fgen
44 Mex_Am.US native -3.703** 0.285
45 Oth_H.US native -3.197** 0.288
46 Oth_NH.US native -4.589** 0.287
47 Wht_NH.US native -1.906** 0.269
year.feth.fgen
48 80.Mex_Am.US native 1.533** 0.291
49 80.Oth_H.US native -0.112 0.295
50 80.Oth_NH.US native 1.074** 0.294
51 80.Wht_NH.US native 1.605** 0.275
52 90.Mex_Am.US native 1.737** 0.292
53 90.Oth_H.US native 0.207 0.297
54 90.Oth_NH.US native 1.517** 0.295
55 90.Wht_NH.US native 2.045** 0.277
ethintct
56 1 13.001** 0.525
57 2 5.541** 0.330
58 3 3.945** 0.353
59 4 4.997** 0.410
60 5 5.277** 0.273
61 year 0.298** 0.018
ethintct.year
62 1.year -0.074** 0.006
63 2.year -0.027** 0.004
64 3.year -0.016** 0.004
65 4.year -0.034** 0.005
66 5.year -0.033** 0.003
67 _cons -31.082** 1.565
----------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 4069.044
Prob > chi2(158) = 0.0000
. display 4069-158*(ln(649821))
1954.2565
. predict 7a
7a invalid name
r(198);
. predict P7a
(option n assumed; predicted number of events)
. gen ID7a=50*(abs((P7a/649821)-(count/649821)))
. table year, contents(sum ID7a) row
----------------------
year | sum(ID7a)
----------+-----------
70 | .112071
80 | .3586141
90 | .3168996
|
Total | .7875847
----------------------
. tabulate meth
meth | Freq. Percent Cum.
------------+-----------------------------------
Blk_NH | 45 20.00 20.00
Mex_Am | 45 20.00 40.00
Oth_H | 45 20.00 60.00
Oth_NH | 45 20.00 80.00
Wht_NH | 45 20.00 100.00
------------+-----------------------------------
Total | 225 100.00
. tabulate meth [fweight=count]
meth | Freq. Percent Cum.
------------+-----------------------------------
Blk_NH | 45,681 7.03 7.03
Mex_Am | 25,294 3.89 10.92
Oth_H | 11,609 1.79 12.71
Oth_NH | 8,100 1.25 13.96
Wht_NH | 559,137 86.04 100.00
------------+-----------------------------------
Total | 649,821 100.00
. tabulate meth [fweight=count], nolab
meth | Freq. Percent Cum.
------------+-----------------------------------
Blk_NH | 45,681 7.03 7.03
Mex_Am | 25,294 3.89 10.92
Oth_H | 11,609 1.79 12.71
Oth_NH | 8,100 1.25 13.96
Wht_NH | 559,137 86.04 100.00
------------+-----------------------------------
Total | 649,821 100.00
. table meth feth, contents (mean ethinct)
variable ethinct not found
r(111);
. table meth feth, contents (mean ethintctt)
variable ethintctt not found
r(111);
. table meth feth, contents (mean ethintct)
--------------------------------------------------
| feth
meth | Blk_NH Mex_Am Oth_H Oth_NH Wht_NH
----------+---------------------------------------
Blk_NH | 1 0 0 0 0
Mex_Am | 0 2 0 0 0
Oth_H | 0 0 3 0 0
Oth_NH | 0 0 0 4 0
Wht_NH | 0 0 0 0 5
--------------------------------------------------
. *And now to return to question 4 with a model specifically tailored to the question of racial intermarriage by immigrant generation.
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year ethinct*mgen ethinct*fgen
variable ethinct not found
r(111);
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year ethintct*mgen ethintct*fgen
Hessian has become unstable or asymmetric (NC)
--Break--
r(1);
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*year ethintct*mgen ethintct*fgen, difficult
----------------------------------------------------------------------------------
Poisson regression
----------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -1576.216
LR chi square: 4502074.862
Model degrees of freedom: 81
Pseudo R-squared: 0.999
Prob: 0.000
----------------------------------------------------------------------------------
nr Effect Coeff s.e.
----------------------------------------------------------------------------------
count
year
1 80 4.666** 0.368
2 90 5.607** 0.369
meth
3 Mex_Am 2.801** 0.241
4 Oth_H 2.995** 0.242
5 Oth_NH 2.593** 0.272
6 Wht_NH 3.812** 0.235
year.meth
7 80.Mex_Am -0.549* 0.231
8 80.Oth_H -0.104 0.233
9 80.Oth_NH -0.486 0.265
10 80.Wht_NH -0.985** 0.222
11 90.Mex_Am -0.661** 0.232
12 90.Oth_H -0.585* 0.234
13 90.Oth_NH -0.800** 0.266
14 90.Wht_NH -1.345** 0.223
mgen
15 US native 4.074** 0.201
year.mgen
16 80.US native -0.896** 0.187
17 90.US native -1.407** 0.188
meth.mgen
18 Mex_Am.US native -1.889** 0.223
19 Oth_H.US native -1.852** 0.226
20 Oth_NH.US native -2.342** 0.263
21 Wht_NH.US native -0.591** 0.209
year.meth.mgen
22 80.Mex_Am.US native 0.386 0.210
23 80.Oth_H.US native -0.788** 0.214
24 80.Oth_NH.US native 0.462 0.255
25 80.Wht_NH.US native 0.675** 0.191
26 90.Mex_Am.US native 0.524* 0.211
27 90.Oth_H.US native -0.353 0.216
28 90.Oth_NH.US native 0.852** 0.256
29 90.Wht_NH.US native 1.089** 0.192
feth
30 Mex_Am 3.468** 0.333
31 Oth_H 3.739** 0.334
32 Oth_NH 4.696** 0.328
33 Wht_NH 4.925** 0.327
year.feth
34 80.Mex_Am -1.074** 0.319
35 80.Oth_H -0.330 0.320
36 80.Oth_NH -0.797* 0.314
37 80.Wht_NH -1.318** 0.310
38 90.Mex_Am -1.271** 0.320
39 90.Oth_H -0.815* 0.321
40 90.Oth_NH -1.403** 0.315
41 90.Wht_NH -1.910** 0.311
fgen
42 US native 4.252** 0.294
year.fgen
43 80.US native -1.522** 0.273
44 90.US native -1.929** 0.275
feth.fgen
45 Mex_Am.US native -2.058** 0.311
46 Oth_H.US native -1.994** 0.314
47 Oth_NH.US native -3.755** 0.314
48 Wht_NH.US native -1.095** 0.299
year.feth.fgen
49 80.Mex_Am.US native 1.514** 0.291
50 80.Oth_H.US native 0.052 0.296
51 80.Oth_NH.US native 1.327** 0.296
52 80.Wht_NH.US native 1.600** 0.275
53 90.Mex_Am.US native 1.630** 0.293
54 90.Oth_H.US native 0.266 0.297
55 90.Oth_NH.US native 1.730** 0.298
56 90.Wht_NH.US native 1.973** 0.277
ethintct
57 1 5.158** 0.225
58 2 3.900** 0.120
59 3 2.422** 0.120
60 4 0.648** 0.160
61 5 1.657** 0.110
ethintct.year
62 1.80 -0.568** 0.170
63 1.90 -1.309** 0.170
64 2.80 -0.243* 0.112
65 2.90 -0.555** 0.112
66 3.80 -0.592** 0.109
67 3.90 -0.448** 0.110
68 4.80 -0.956** 0.139
69 4.90 -1.103** 0.140
70 5.80 -0.578** 0.092
71 5.90 -0.831** 0.093
ethintct.mgen
72 1.US native 0.989** 0.094
73 2.US native -0.176** 0.037
74 3.US native 0.329** 0.044
75 4.US native 1.107** 0.074
76 5.US native 0.759** 0.049
ethintct.fgen
77 1.US native 1.607** 0.129
78 2.US native -0.134** 0.047
79 3.US native 0.512** 0.048
80 4.US native 1.892** 0.064
81 5.US native 0.758** 0.047
82 _cons -7.649** 0.386
----------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 1820.433
Prob > chi2(143) = 0.0000
. *US nativity for either or both spouses increases endogamy for category 4 (other non Hispanic) category 1 (white) and category 5 (black) in that order.
. *It is important to take ethintct*year into account before looking at the ethnintct*gen terms, because ethnic endogamy and ethnic and generational profile of the population change a lot over time.
. desmat: poisson count year*meth*mgen year*feth*fgen ethintct*mgen ethintct*fgen, difficult
----------------------------------------------------------------------------------
Poisson regression
----------------------------------------------------------------------------------
Dependent variable count
Optimization: ml
Number of observations: 225
Initial log likelihood: -2252613.647
Log likelihood: -2101.794
LR chi square: 4501023.706
Model degrees of freedom: 71
Pseudo R-squared: 0.999
Prob: 0.000
----------------------------------------------------------------------------------
nr Effect Coeff s.e.
----------------------------------------------------------------------------------
count
year
1 80 4.183** 0.330
2 90 4.491** 0.332
meth
3 Mex_Am 2.655** 0.224
4 Oth_H 2.829** 0.226
5 Oth_NH 2.315** 0.258
6 Wht_NH 3.869** 0.212
year.meth
7 80.Mex_Am -0.412 0.214
8 80.Oth_H -0.054 0.217
9 80.Oth_NH -0.303 0.253
10 80.Wht_NH -1.085** 0.196
11 90.Mex_Am -0.522* 0.216
12 90.Oth_H -0.325 0.219
13 90.Oth_NH -0.444 0.254
14 90.Wht_NH -1.452** 0.198
mgen
15 US native 4.053** 0.199
year.mgen
16 80.US native -0.914** 0.187
17 90.US native -1.450** 0.188
meth.mgen
18 Mex_Am.US native -1.906** 0.221
19 Oth_H.US native -1.824** 0.224
20 Oth_NH.US native -2.047** 0.259
21 Wht_NH.US native -0.574** 0.207
year.meth.mgen
22 80.Mex_Am.US native 0.409 0.210
23 80.Oth_H.US native -0.816** 0.214
24 80.Oth_NH.US native 0.211 0.254
25 80.Wht_NH.US native 0.685** 0.190
26 90.Mex_Am.US native 0.576** 0.211
27 90.Oth_H.US native -0.371 0.215
28 90.Oth_NH.US native 0.554* 0.254
29 90.Wht_NH.US native 1.121** 0.192
feth
30 Mex_Am 3.010** 0.307
31 Oth_H 3.211** 0.309
32 Oth_NH 3.946** 0.304
33 Wht_NH 4.632** 0.296
year.feth
34 80.Mex_Am -0.837** 0.294
35 80.Oth_H -0.129 0.297
36 80.Oth_NH -0.364 0.292
37 80.Wht_NH -1.293** 0.279
38 90.Mex_Am -0.632* 0.295
39 90.Oth_H 0.004 0.299
40 90.Oth_NH -0.364 0.294
41 90.Wht_NH -1.483** 0.281
fgen
42 US native 4.193** 0.289
year.fgen
43 80.US native -1.575** 0.273
44 90.US native -2.046** 0.275
feth.fgen
45 Mex_Am.US native -2.021** 0.306
46 Oth_H.US native -1.892** 0.309
47 Oth_NH.US native -3.334** 0.307
48 Wht_NH.US native -1.027** 0.294
year.feth.fgen
49 80.Mex_Am.US native 1.572** 0.291
50 80.Oth_H.US native 0.027 0.295
51 80.Oth_NH.US native 1.033** 0.294
52 80.Wht_NH.US native 1.647** 0.275
53 90.Mex_Am.US native 1.748** 0.293
54 90.Oth_H.US native 0.288 0.297
55 90.Oth_NH.US native 1.408** 0.296
56 90.Wht_NH.US native 2.079** 0.277
ethintct
57 1 4.162** 0.155
58 2 3.459** 0.058
59 3 1.844** 0.059
60 4 -0.382** 0.094
61 5 1.005** 0.069
ethintct.mgen
62 1.US native 1.042** 0.094
63 2.US native -0.132** 0.037
64 3.US native 0.416** 0.043
65 4.US native 1.147** 0.073
66 5.US native 0.772** 0.049
ethintct.fgen
67 1.US native 1.749** 0.128
68 2.US native -0.107* 0.047
69 3.US native 0.595** 0.048
70 4.US native 1.913** 0.064
71 5.US native 0.756** 0.047
72 _cons -6.785** 0.349
----------------------------------------------------------------------------------
* p < .05
** p < .01
. poisgof
Goodness-of-fit chi2 = 2871.588
Prob > chi2(153) = 0.0000
. *but even without ethintct*year, we get the same basic result for ethnitct*mgen and ethintct*fgen.
. table meth feth, contents(mean ethintct)
--------------------------------------------------
| feth
meth | Blk_NH Mex_Am Oth_H Oth_NH Wht_NH
----------+---------------------------------------
Blk_NH | 1 0 0 0 0
Mex_Am | 0 2 0 0 0
Oth_H | 0 0 3 0 0
Oth_NH | 0 0 0 4 0
Wht_NH | 0 0 0 0 5
--------------------------------------------------
. *why do some of the more complex models only converge with the difficult option?
.
. tabulate count
Frequency | Freq. Percent Cum.
------------+-----------------------------------
0 | 8 3.56 3.56
1 | 7 3.11 6.67
2 | 7 3.11 9.78
3 | 8 3.56 13.33
5 | 9 4.00 17.33
6 | 4 1.78 19.11
7 | 5 2.22 21.33
8 | 2 0.89 22.22
9 | 1 0.44 22.67
10 | 1 0.44 23.11
11 | 2 0.89 24.00
12 | 7 3.11 27.11
13 | 1 0.44 27.56
14 | 4 1.78 29.33
15 | 1 0.44 29.78
16 | 1 0.44 30.22
17 | 1 0.44 30.67
19 | 1 0.44 31.11
20 | 4 1.78 32.89
21 | 2 0.89 33.78
22 | 1 0.44 34.22
23 | 1 0.44 34.67
25 | 1 0.44 35.11
26 | 4 1.78 36.89
27 | 1 0.44 37.33
29 | 1 0.44 37.78
33 | 3 1.33 39.11
34 | 1 0.44 39.56
35 | 3 1.33 40.89
36 | 2 0.89 41.78
38 | 2 0.89 42.67
40 | 2 0.89 43.56
41 | 1 0.44 44.00
42 | 1 0.44 44.44
43 | 3 1.33 45.78
45 | 1 0.44 46.22
46 | 1 0.44 46.67
47 | 1 0.44 47.11
50 | 2 0.89 48.00
54 | 1 0.44 48.44
56 | 1 0.44 48.89
60 | 2 0.89 49.78
61 | 1 0.44 50.22
62 | 1 0.44 50.67
64 | 1 0.44 51.11
65 | 1 0.44 51.56
66 | 3 1.33 52.89
67 | 1 0.44 53.33
68 | 3 1.33 54.67
71 | 1 0.44 55.11
76 | 1 0.44 55.56
78 | 3 1.33 56.89
79 | 1 0.44 57.33
80 | 2 0.89 58.22
81 | 1 0.44 58.67
85 | 2 0.89 59.56
88 | 1 0.44 60.00
91 | 1 0.44 60.44
94 | 1 0.44 60.89
95 | 1 0.44 61.33
96 | 1 0.44 61.78
104 | 1 0.44 62.22
105 | 1 0.44 62.67
107 | 1 0.44 63.11
109 | 2 0.89 64.00
121 | 1 0.44 64.44
122 | 1 0.44 64.89
123 | 1 0.44 65.33
126 | 1 0.44 65.78
129 | 1 0.44 66.22
130 | 1 0.44 66.67
131 | 1 0.44 67.11
132 | 1 0.44 67.56
134 | 1 0.44 68.00
138 | 1 0.44 68.44
139 | 1 0.44 68.89
144 | 1 0.44 69.33
147 | 1 0.44 69.78
148 | 1 0.44 70.22
156 | 1 0.44 70.67
158 | 1 0.44 71.11
186 | 1 0.44 71.56
224 | 1 0.44 72.00
230 | 1 0.44 72.44
232 | 2 0.89 73.33
239 | 1 0.44 73.78
246 | 1 0.44 74.22
257 | 1 0.44 74.67
263 | 1 0.44 75.11
296 | 1 0.44 75.56
315 | 1 0.44 76.00
329 | 1 0.44 76.44
381 | 1 0.44 76.89
391 | 1 0.44 77.33
401 | 1 0.44 77.78
405 | 1 0.44 78.22
413 | 1 0.44 78.67
481 | 1 0.44 79.11
482 | 1 0.44 79.56
627 | 1 0.44 80.00
628 | 1 0.44 80.44
632 | 1 0.44 80.89
640 | 1 0.44 81.33
686 | 1 0.44 81.78
756 | 1 0.44 82.22
773 | 1 0.44 82.67
789 | 1 0.44 83.11
809 | 1 0.44 83.56
878 | 1 0.44 84.00
914 | 1 0.44 84.44
919 | 1 0.44 84.89
1006 | 1 0.44 85.33
1012 | 1 0.44 85.78
1083 | 1 0.44 86.22
1135 | 1 0.44 86.67
1163 | 1 0.44 87.11
1176 | 1 0.44 87.56
1197 | 1 0.44 88.00
1227 | 1 0.44 88.44
1392 | 1 0.44 88.89
1430 | 1 0.44 89.33
1454 | 1 0.44 89.78
1492 | 1 0.44 90.22
1514 | 1 0.44 90.67
1527 | 1 0.44 91.11
1545 | 1 0.44 91.56
1558 | 1 0.44 92.00
1586 | 1 0.44 92.44
1653 | 1 0.44 92.89
2171 | 1 0.44 93.33
2204 | 1 0.44 93.78
2210 | 1 0.44 94.22
2556 | 1 0.44 94.67
3629 | 1 0.44 95.11
3752 | 1 0.44 95.56
4596 | 1 0.44 96.00
5019 | 1 0.44 96.44
5020 | 1 0.44 96.89
5151 | 1 0.44 97.33
7116 | 1 0.44 97.78
12005 | 1 0.44 98.22
24628 | 1 0.44 98.67
54331 | 1 0.44 99.11
188975 | 1 0.44 99.56
280562 | 1 0.44 100.00
------------+-----------------------------------
Total | 225 100.00
. *A fifth of the dataset has fewer than 10 counts per cell.
. exit, clear