Hello,
I am working on an ologit model that is exploring changes in a survey respondent's satisfaction with their financial condition based in part on their income levels related to Medicaid and tax credits/subsidies in health benefit exchanges. Here is my model:
The next step that I am working on is to look at the results of margins by specific income level year groupings across 3 income eligibility groups and years. The first command yields results:
But when I move to my next income group, I get a not estimable result that I cannot figure out:
Previously, about a month ago, I ran this same ologit model and marings commands which produced results. The only differences between then and now are: 1) I updated Stata from 16 to 17 and 2) deleted 83 observations due to responses being out of range with do not know and prefer not to answer. Any insight is appreciated.
I am working on an ologit model that is exploring changes in a survey respondent's satisfaction with their financial condition based in part on their income levels related to Medicaid and tax credits/subsidies in health benefit exchanges. Here is my model:
Code:
. svy: ologit satisfact_fin_con mcaid_exp eng_d eng_d_mexp gender i.ethnicity i.education c.income2012##c.income2012 c.income2015##c.income2015 c.income2018##c.income2018 i.living_arr_and_dep_kids full_time_employment unemployed retirement i.state h1 hi_under55 Y2012 Y2015 Y2018
(running ologit on estimation sample)
Survey: Ordered logistic regression
Number of strata = 1 Number of obs = 14,221
Number of PSUs = 14,221 Population size = 13,787.025
Design df = 14,220
F(75, 14146) = .
Prob > F = .
-----------------------------------------------------------------------------------------------------------------------
| Linearized
satisfact_fin_con | Coefficient std. err. t P>|t| [95% conf. interval]
------------------------------------------------------+----------------------------------------------------------------
mcaid_exp | .1646864 .1034007 1.59 0.111 -.0379924 .3673652
eng_d | -.0615908 .159987 -0.38 0.700 -.3751862 .2520047
eng_d_mexp | -.0904735 .1796805 -0.50 0.615 -.4426709 .2617238
gender | -.1703788 .0374672 -4.55 0.000 -.2438193 -.0969382
|
ethnicity |
Black non-Hispanic | -.2072806 .0694167 -2.99 0.003 -.3433465 -.0712147
Hispanic any race | .1789224 .0930218 1.92 0.054 -.0034126 .3612574
Asian non-Hispanic | -.0258495 .1193996 -0.22 0.829 -.2598883 .2081893
Other non-Hispanic (American Indian, Other, 2+ et..) | -.3363047 .1096566 -3.07 0.002 -.551246 -.1213635
|
education |
HS Grad | .2893673 .1314109 2.20 0.028 .0317848 .5469497
Some College | .132868 .1304964 1.02 0.309 -.1229221 .3886581
College Grad | .2768922 .1345936 2.06 0.040 .0130712 .5407133
Graduate Degree | .3131309 .1382932 2.26 0.024 .0420582 .5842037
|
income2012 | .000023 2.03e-06 11.34 0.000 .000019 .0000269
|
c.income2012#c.income2012 | -4.62e-11 8.22e-12 -5.62 0.000 -6.23e-11 -3.01e-11
|
income2015 | .0000285 2.15e-06 13.27 0.000 .0000243 .0000327
|
c.income2015#c.income2015 | -7.30e-11 9.29e-12 -7.85 0.000 -9.12e-11 -5.48e-11
|
income2018 | .0000307 2.29e-06 13.39 0.000 .0000262 .0000351
|
c.income2018#c.income2018 | -7.55e-11 1.01e-11 -7.50 0.000 -9.53e-11 -5.58e-11
|
living_arr_and_dep_kids |
1 adult and kid(s) | .087429 .138907 0.63 0.529 -.1848469 .3597049
multiple adults 0 kids | -.1008708 .0517836 -1.95 0.051 -.2023734 .0006318
multiple adults and kid(s) | -.4064206 .0641402 -6.34 0.000 -.5321439 -.2806974
|
full_time_employment | -.0373899 .0474741 -0.79 0.431 -.1304452 .0556655
unemployed | -.5802745 .0823599 -7.05 0.000 -.7417108 -.4188382
retirement | .6634571 .0480713 13.80 0.000 .569231 .7576831
|
state |
Alaska | .1538897 .1760655 0.87 0.382 -.1912216 .4990011
Arizona | .1245345 .1930407 0.65 0.519 -.2538505 .5029195
Arkansas | -.2068757 .1744907 -1.19 0.236 -.5489002 .1351489
California | -.0172462 .1913838 -0.09 0.928 -.3923835 .3578911
Colorado | -.1777846 .1807532 -0.98 0.325 -.5320844 .1765152
Connecticut | -.1672435 .196774 -0.85 0.395 -.5529464 .2184593
Delaware | -.1971523 .1927451 -1.02 0.306 -.5749579 .1806534
District of Columbia | .1646567 .2132393 0.77 0.440 -.2533203 .5826337
Florida | .0692714 .1685594 0.41 0.681 -.2611271 .3996699
Georgia | -.1744549 .1670467 -1.04 0.296 -.5018883 .1529784
Hawaii | -.0304913 .2121641 -0.14 0.886 -.4463607 .3853781
Idaho | .2478786 .1989769 1.25 0.213 -.1421422 .6378994
Illinois | -.2319925 .1820535 -1.27 0.203 -.5888411 .1248562
Indiana | .2669032 .1806815 1.48 0.140 -.0872561 .6210625
Iowa | .2057265 .1849483 1.11 0.266 -.1567965 .5682494
Kansas | -.1776296 .1708918 -1.04 0.299 -.5125999 .1573407
Kentucky | .1653678 .1799308 0.92 0.358 -.1873202 .5180557
Louisiana | -.1946951 .1729925 -1.13 0.260 -.5337829 .1443927
Maine | .0247627 .1701336 0.15 0.884 -.3087214 .3582468
Maryland | -.3649838 .1906788 -1.91 0.056 -.7387392 .0087716
Massachusetts | -.1235645 .1991212 -0.62 0.535 -.5138682 .2667391
Michigan | .2547052 .1898303 1.34 0.180 -.117387 .6267973
Minnesota | .0610862 .1978241 0.31 0.757 -.3266749 .4488473
Mississippi | -.0527727 .1631322 -0.32 0.746 -.3725332 .2669878
Missouri | .1649411 .1774707 0.93 0.353 -.1829246 .5128069
Montana | .2149899 .1628347 1.32 0.187 -.1041875 .5341673
Nebraska | .2146402 .1744895 1.23 0.219 -.127382 .5566624
Nevada | .1408843 .177398 0.79 0.427 -.206839 .4886076
New Hampshire | .1156075 .1859118 0.62 0.534 -.2488041 .480019
New Jersey | -.3679061 .1867893 -1.97 0.049 -.7340376 -.0017746
New Mexico | .0306712 .1895149 0.16 0.871 -.3408028 .4021451
New York | .0323792 .187452 0.17 0.863 -.3350512 .3998096
North Carolina | .0651057 .1677474 0.39 0.698 -.2637011 .3939126
North Dakota | .1516464 .178594 0.85 0.396 -.1984212 .501714
Ohio | .0250083 .1848407 0.14 0.892 -.3373037 .3873202
Oklahoma | .0063428 .1657666 0.04 0.969 -.3185814 .331267
Oregon | .0246889 .1664366 0.15 0.882 -.3015486 .3509263
Pennsylvania | -.2375424 .1765484 -1.35 0.178 -.5836004 .1085155
Rhode Island | .0370566 .1809652 0.20 0.838 -.3176589 .391772
South Carolina | -.0746881 .1667144 -0.45 0.654 -.4014701 .2520938
South Dakota | .3004683 .1699385 1.77 0.077 -.0326333 .6335699
Tennessee | .1044944 .1737673 0.60 0.548 -.2361123 .4451011
Texas | -.0364918 .1742135 -0.21 0.834 -.3779731 .3049895
Utah | .1578976 .1832772 0.86 0.389 -.2013496 .5171449
Vermont | .1289547 .1882139 0.69 0.493 -.2399691 .4978786
Virginia | -.1747913 .1764976 -0.99 0.322 -.5207497 .1711672
Washington | .0195483 .169052 0.12 0.908 -.3118158 .3509124
West Virginia | -.0328476 .1762213 -0.19 0.852 -.3782645 .3125693
Wisconsin | -.0327713 .1753222 -0.19 0.852 -.3764257 .3108831
Wyoming | .172028 .1554212 1.11 0.268 -.1326179 .4766738
|
h1 | -.4917407 .0686699 -7.16 0.000 -.6263427 -.3571387
hi_under55 | .4188247 .5985703 0.70 0.484 -.7544513 1.592101
Y2012 | -.112137 .1479055 -0.76 0.448 -.4020511 .1777772
Y2015 | .0166794 .1310208 0.13 0.899 -.2401386 .2734974
Y2018 | 0 (omitted)
------------------------------------------------------+----------------------------------------------------------------
/cut1 | -.2341094 .7699423 -1.743297 1.275078
/cut2 | 1.196162 .7701736 -.3134793 2.705803
/cut3 | 3.500011 .771525 1.987722 5.012301
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Code:
. margins if income2012<26614.2, dydx(income2012) predict(xb)
Average marginal effects
Number of strata = 1 Number of obs = 10,465
Number of PSUs = 14,221 Population size = 13,787.025
Model VCE: Linearized Design df = 14,220
Expression: Linear prediction (cutpoints excluded), predict(xb)
dy/dx wrt: income2012
------------------------------------------------------------------------------
| Delta-method
| dy/dx std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
income2012 | .0000228 2.00e-06 11.41 0.000 .0000189 .0000267
------------------------------------------------------------------------------
Code:
. margins if income2012>26614.2 & income2012<77142.61, dydx(income2012) predict(xb)
Average marginal effects
Number of strata = 1 Number of obs = 1,198
Number of PSUs = 14,221 Population size = 13,787.025
Model VCE: Linearized Design df = 14,220
Expression: Linear prediction (cutpoints excluded), predict(xb)
dy/dx wrt: income2012
------------------------------------------------------------------------------
| Delta-method
| dy/dx std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
income2012 | . (not estimable)
------------------------------------------------------------------------------
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