------------------------------------------------------------------------------- log: c:\bill\spring2011\helmet_law_data.log log type: text opened on: 5 Apr 2011, 08:21:59 . * list variables in the data; . desc; Contains data from helmet_law_data.dta obs: 714 vars: 9 5 Apr 2011 08:16 size: 50,694 (99.8% of memory free) ------------------------------------------------------------------------------- storage display value variable name type format label variable label ------------------------------------------------------------------------------- year double %8.0g year pci_r float %9.0g real per capita income pop_adults long %12.0g adult population mc_deaths int %8.0g motor cycle deaths state str20 %20s 2 digit state code, AL, AR, AZ.... mc_helmet_law byte %8.0g dummy variable, =1 if universal helmet law in effect, 0 otherwise pop1630 double %12.0g population aged 16 to 30 mc_deaths1630 double %12.0g motor cycle deaths, aged 16 to 30 fips double %12.0g 2 digit state code to identify state ------------------------------------------------------------------------------- Sorted by: . * get the log per capita income and log population; . gen pci_rl=ln(pci_r); . gen pop1630l=ln(pop1630); . * look at distribution of counts; . tab mc_deaths1630; motor cycle | deaths, | aged 16 to | 30 | Freq. Percent Cum. ------------+----------------------------------- 0 | 12 1.68 1.68 1 | 27 3.78 5.46 2 | 27 3.78 9.24 3 | 30 4.20 13.45 4 | 42 5.88 19.33 5 | 27 3.78 23.11 6 | 28 3.92 27.03 7 | 23 3.22 30.25 8 | 27 3.78 34.03 9 | 35 4.90 38.94 10 | 21 2.94 41.88 11 | 13 1.82 43.70 12 | 15 2.10 45.80 13 | 13 1.82 47.62 14 | 19 2.66 50.28 15 | 15 2.10 52.38 16 | 14 1.96 54.34 17 | 16 2.24 56.58 18 | 24 3.36 59.94 19 | 12 1.68 61.62 20 | 16 2.24 63.87 21 | 10 1.40 65.27 22 | 21 2.94 68.21 23 | 16 2.24 70.45 24 | 10 1.40 71.85 25 | 9 1.26 73.11 26 | 9 1.26 74.37 27 | 11 1.54 75.91 28 | 11 1.54 77.45 29 | 9 1.26 78.71 30 | 7 0.98 79.69 31 | 8 1.12 80.81 32 | 5 0.70 81.51 33 | 6 0.84 82.35 34 | 6 0.84 83.19 35 | 2 0.28 83.47 36 | 2 0.28 83.75 38 | 6 0.84 84.59 39 | 3 0.42 85.01 41 | 5 0.70 85.71 42 | 1 0.14 85.85 43 | 5 0.70 86.55 44 | 6 0.84 87.39 45 | 1 0.14 87.54 46 | 4 0.56 88.10 47 | 1 0.14 88.24 48 | 1 0.14 88.38 49 | 3 0.42 88.80 50 | 3 0.42 89.22 51 | 5 0.70 89.92 52 | 3 0.42 90.34 53 | 6 0.84 91.18 54 | 5 0.70 91.88 55 | 4 0.56 92.44 57 | 2 0.28 92.72 58 | 3 0.42 93.14 59 | 2 0.28 93.42 60 | 2 0.28 93.70 62 | 1 0.14 93.84 63 | 2 0.28 94.12 65 | 2 0.28 94.40 66 | 1 0.14 94.54 69 | 1 0.14 94.68 70 | 2 0.28 94.96 71 | 1 0.14 95.10 72 | 2 0.28 95.38 73 | 1 0.14 95.52 74 | 1 0.14 95.66 76 | 3 0.42 96.08 77 | 2 0.28 96.36 78 | 1 0.14 96.50 79 | 2 0.28 96.78 80 | 1 0.14 96.92 83 | 1 0.14 97.06 85 | 2 0.28 97.34 87 | 1 0.14 97.48 90 | 1 0.14 97.62 93 | 1 0.14 97.76 97 | 1 0.14 97.90 100 | 1 0.14 98.04 103 | 1 0.14 98.18 104 | 1 0.14 98.32 109 | 2 0.28 98.60 110 | 1 0.14 98.74 111 | 1 0.14 98.88 130 | 2 0.28 99.16 132 | 1 0.14 99.30 136 | 1 0.14 99.44 142 | 1 0.14 99.58 150 | 1 0.14 99.72 181 | 1 0.14 99.86 324 | 1 0.14 100.00 ------------+----------------------------------- Total | 714 100.00 . * generate year and fips effects; . xi i.year i.fips; i.year _Iyear_1991-2004 (naturally coded; _Iyear_1991 omitted) i.fips _Ifips_1-56 (naturally coded; _Ifips_1 omitted) . * get local list for right hand side variables; . * xlist1 is for the regular models, xlist2 is for; . * the conditional poisson/negative binomial models; . local xlist1 _If* _Iy* pci_rl pop1630l mc_helmet_law; . local xlist2 _Iy* pci_rl pop1630l mc_helmet_law; . * run a fixed-effect poisson model; . * the conditioning variable is stfip; . * fe is the option for fixed effects; . * can also ask for random effects; . xtpoisson mc_deaths1630 `xlist2', i(fips) fe; Iteration 0: log likelihood = -2171.2372 Iteration 1: log likelihood = -1844.8995 Iteration 2: log likelihood = -1838.2985 Iteration 3: log likelihood = -1838.2944 Iteration 4: log likelihood = -1838.2944 Conditional fixed-effects Poisson regression Number of obs = 714 Group variable: fips Number of groups = 51 Obs per group: min = 14 avg = 14.0 max = 14 Wald chi2(16) = 692.91 Log likelihood = -1838.2944 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ mc_deat~1630 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _Iyear_1992 | -.2628832 .0384162 -6.84 0.000 -.3381775 -.1875889 _Iyear_1993 | -.2081264 .038693 -5.38 0.000 -.2839633 -.1322896 _Iyear_1994 | -.3357597 .0414838 -8.09 0.000 -.4170665 -.2544529 _Iyear_1995 | -.4129979 .0442316 -9.34 0.000 -.4996903 -.3263055 _Iyear_1996 | -.5798579 .0496996 -11.67 0.000 -.6772673 -.4824485 _Iyear_1997 | -.7194087 .0575535 -12.50 0.000 -.8322116 -.6066059 _Iyear_1998 | -.7829745 .0720463 -10.87 0.000 -.9241827 -.6417662 _Iyear_1999 | -.8179211 .0782733 -10.45 0.000 -.971334 -.6645083 _Iyear_2000 | -.8199416 .0896638 -9.14 0.000 -.9956795 -.6442038 _Iyear_2001 | -.6859323 .08771 -7.82 0.000 -.8578407 -.5140239 _Iyear_2002 | -.7571016 .0853388 -8.87 0.000 -.9243626 -.5898407 _Iyear_2003 | -.6558562 .084304 -7.78 0.000 -.821089 -.4906233 _Iyear_2004 | -.642001 .0946942 -6.78 0.000 -.8275982 -.4564037 pci_rl | 1.931553 .471095 4.10 0.000 1.008224 2.854883 pop1630l | .4711974 .1919719 2.45 0.014 .0949394 .8474554 mc_helmet_~w | -.3869036 .0321337 -12.04 0.000 -.4498845 -.3239226 ------------------------------------------------------------------------------ . * run a negative binomial fixed effects; . * the conditioning variable is stfip; . xtnbreg mc_deaths1630 `xlist2', i(fips) fe; Iteration 0: log likelihood = -1848.6171 Iteration 1: log likelihood = -1817.2214 Iteration 2: log likelihood = -1813.7804 Iteration 3: log likelihood = -1813.7045 Iteration 4: log likelihood = -1813.7045 Conditional FE negative binomial regression Number of obs = 714 Group variable: fips Number of groups = 51 Obs per group: min = 14 avg = 14.0 max = 14 Wald chi2(16) = 338.30 Log likelihood = -1813.7045 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ mc_deat~1630 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _Iyear_1992 | -.2332995 .0492203 -4.74 0.000 -.3297695 -.1368294 _Iyear_1993 | -.2027734 .0485023 -4.18 0.000 -.2978361 -.1077106 _Iyear_1994 | -.3316033 .0522424 -6.35 0.000 -.4339965 -.2292101 _Iyear_1995 | -.3948847 .0552161 -7.15 0.000 -.5031063 -.2866631 _Iyear_1996 | -.5532594 .0609925 -9.07 0.000 -.6728025 -.4337163 _Iyear_1997 | -.7110721 .0694895 -10.23 0.000 -.847269 -.5748753 _Iyear_1998 | -.7412649 .0852808 -8.69 0.000 -.9084121 -.5741176 _Iyear_1999 | -.7861217 .0925206 -8.50 0.000 -.9674588 -.6047846 _Iyear_2000 | -.759475 .1055561 -7.19 0.000 -.9663612 -.5525887 _Iyear_2001 | -.6221927 .10323 -6.03 0.000 -.8245197 -.4198656 _Iyear_2002 | -.7068142 .1014209 -6.97 0.000 -.9055955 -.5080328 _Iyear_2003 | -.6191591 .1018211 -6.08 0.000 -.8187248 -.4195934 _Iyear_2004 | -.575905 .1127321 -5.11 0.000 -.796856 -.3549541 pci_rl | 1.706626 .535652 3.19 0.001 .6567673 2.756484 pop1630l | .1721916 .1845149 0.93 0.351 -.189451 .5338342 mc_helmet_~w | -.3476735 .0447335 -7.77 0.000 -.4353494 -.2599975 _cons | -15.35193 5.865379 -2.62 0.009 -26.84786 -3.856002 ------------------------------------------------------------------------------ . * compare to a nbreg model with all the fips; . * effects added. pick the nbreg model with a ; . * constant dispersion factor. in this case; . * actively add in fips fips; . nbreg mc_deaths1630 `xlist1', dispersion(constant); Fitting Poisson model: Iteration 0: log likelihood = -12619.428 Iteration 1: log likelihood = -4528.7595 Iteration 2: log likelihood = -2136.3574 Iteration 3: log likelihood = -2019.4384 Iteration 4: log likelihood = -2018.7586 Iteration 5: log likelihood = -2018.7586 Fitting constant-only model: Iteration 0: log likelihood = -5386.246 Iteration 1: log likelihood = -3534.2051 Iteration 2: log likelihood = -2942.1067 Iteration 3: log likelihood = -2929.4485 Iteration 4: log likelihood = -2929.3789 Iteration 5: log likelihood = -2929.3789 Fitting full model: Iteration 0: log likelihood = -2929.3789 (not concave) Iteration 1: log likelihood = -2861.6637 (not concave) Iteration 2: log likelihood = -2769.2279 (not concave) Iteration 3: log likelihood = -2519.7433 (not concave) Iteration 4: log likelihood = -2231.0544 Iteration 5: log likelihood = -2075.6852 Iteration 6: log likelihood = -2012.2648 Iteration 7: log likelihood = -2006.7975 Iteration 8: log likelihood = -2006.7183 Iteration 9: log likelihood = -2006.7183 Negative binomial regression Number of obs = 714 LR chi2(66) = 1845.32 Dispersion = constant Prob > chi2 = 0.0000 Log likelihood = -2006.7183 Pseudo R2 = 0.3150 ------------------------------------------------------------------------------ mc_deat~1630 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _Ifips_2 | -1.995348 .4867883 -4.10 0.000 -2.949435 -1.04126 _Ifips_4 | -.0067781 .1011705 -0.07 0.947 -.2050686 .1915124 _Ifips_5 | -.3806699 .1838336 -2.07 0.038 -.7409771 -.0203628 _Ifips_6 | .4150221 .4796117 0.87 0.387 -.5249997 1.355044 _Ifips_8 | -.6629331 .1665118 -3.98 0.000 -.9892903 -.336576 _Ifips_9 | -1.07746 .2885637 -3.73 0.000 -1.643034 -.5118855 _Ifips_10 | -1.507366 .4372933 -3.45 0.001 -2.364445 -.6502866 _Ifips_11 | -1.851702 .5274634 -3.51 0.000 -2.885511 -.8178929 _Ifips_12 | .6022014 .2762775 2.18 0.029 .0607075 1.143695 _Ifips_13 | -.0060987 .1786765 -0.03 0.973 -.3562981 .3441008 _Ifips_15 | -.9746018 .3217325 -3.03 0.002 -1.605186 -.3440177 _Ifips_16 | -.9841772 .3297825 -2.98 0.003 -1.630539 -.3378154 _Ifips_17 | -.2351275 .27261 -0.86 0.388 -.7694334 .2991784 _Ifips_18 | -.1552345 .1253821 -1.24 0.216 -.400979 .09051 _Ifips_19 | -.6310025 .165371 -3.82 0.000 -.9551237 -.3068813 _Ifips_20 | -.856375 .1822942 -4.70 0.000 -1.213665 -.4990849 _Ifips_21 | -.2387803 .1113267 -2.14 0.032 -.4569766 -.0205839 _Ifips_22 | -.2174301 .1082608 -2.01 0.045 -.4296173 -.0052429 _Ifips_23 | -.7907728 .318653 -2.48 0.013 -1.415321 -.1662245 _Ifips_24 | -.6381521 .2087611 -3.06 0.002 -1.047316 -.228988 _Ifips_25 | -.8447458 .2441298 -3.46 0.001 -1.323231 -.3662602 _Ifips_26 | -.1649515 .2211161 -0.75 0.456 -.5983311 .2684281 _Ifips_27 | -1.042823 .1685041 -6.19 0.000 -1.373085 -.7125614 _Ifips_28 | -.3034165 .1793408 -1.69 0.091 -.654918 .0480849 _Ifips_29 | -.3050951 .1276527 -2.39 0.017 -.5552898 -.0549005 _Ifips_30 | -.801726 .4083817 -1.96 0.050 -1.602139 -.0013126 _Ifips_31 | -1.34903 .2855615 -4.72 0.000 -1.90872 -.7893399 _Ifips_32 | -.799535 .2652035 -3.01 0.003 -1.319324 -.2797458 _Ifips_33 | -1.220286 .3494121 -3.49 0.000 -1.905121 -.5354505 _Ifips_34 | -.7538896 .2785625 -2.71 0.007 -1.299862 -.2079171 _Ifips_35 | -.381562 .2488125 -1.53 0.125 -.8692255 .1061015 _Ifips_36 | -.1030466 .3776932 -0.27 0.785 -.8433117 .6372185 _Ifips_37 | .372149 .1629914 2.28 0.022 .0526918 .6916062 _Ifips_38 | -1.511206 .4789351 -3.16 0.002 -2.449901 -.5725101 _Ifips_39 | -.0171986 .2276007 -0.08 0.940 -.4632877 .4288905 _Ifips_40 | -.4051258 .1320179 -3.07 0.002 -.6638761 -.1463756 _Ifips_41 | -.7167952 .1583295 -4.53 0.000 -1.027115 -.4064751 _Ifips_42 | .1759052 .2486449 0.71 0.479 -.3114298 .6632402 _Ifips_44 | -1.585095 .3741623 -4.24 0.000 -2.318439 -.8517503 _Ifips_45 | .2302458 .1027393 2.24 0.025 .0288804 .4316112 _Ifips_46 | -1.293822 .4456396 -2.90 0.004 -2.167259 -.4203839 _Ifips_47 | .1822989 .1142921 1.60 0.111 -.0417095 .4063073 _Ifips_48 | .3479484 .3518468 0.99 0.323 -.3416587 1.037555 _Ifips_49 | -.5823156 .1972992 -2.95 0.003 -.969015 -.1956162 _Ifips_50 | -1.052194 .4783367 -2.20 0.028 -1.989717 -.1146715 _Ifips_51 | -.6244868 .1988879 -3.14 0.002 -1.0143 -.2346736 _Ifips_53 | -.6334727 .175241 -3.61 0.000 -.9769388 -.2900066 _Ifips_54 | -.0607456 .2421456 -0.25 0.802 -.5353423 .4138512 _Ifips_55 | -.427415 .1293894 -3.30 0.001 -.6810137 -.1738164 _Ifips_56 | -1.782767 .553078 -3.22 0.001 -2.86678 -.6987541 _Iyear_1992 | -.2553753 .0435847 -5.86 0.000 -.3407997 -.1699509 _Iyear_1993 | -.2026962 .0438694 -4.62 0.000 -.2886787 -.1167137 _Iyear_1994 | -.3307537 .0470074 -7.04 0.000 -.4228864 -.2386209 _Iyear_1995 | -.4059678 .0500748 -8.11 0.000 -.5041126 -.3078231 _Iyear_1996 | -.570698 .0562367 -10.15 0.000 -.6809199 -.460476 _Iyear_1997 | -.7116923 .0651313 -10.93 0.000 -.8393472 -.5840373 _Iyear_1998 | -.7741427 .0814752 -9.50 0.000 -.9338312 -.6144542 _Iyear_1999 | -.8088591 .0885664 -9.13 0.000 -.982446 -.6352721 _Iyear_2000 | -.8113763 .1014678 -8.00 0.000 -1.010249 -.612503 _Iyear_2001 | -.675779 .099148 -6.82 0.000 -.8701054 -.4814525 _Iyear_2002 | -.7469265 .0965931 -7.73 0.000 -.9362456 -.5576074 _Iyear_2003 | -.6466251 .0954392 -6.78 0.000 -.8336826 -.4595676 _Iyear_2004 | -.6317418 .1069743 -5.91 0.000 -.8414077 -.422076 pci_rl | 1.899044 .5323889 3.57 0.000 .8555805 2.942507 pop1630l | .4759465 .2165772 2.20 0.028 .0514629 .90043 mc_helmet_~w | -.3856393 .0364927 -10.57 0.000 -.4571636 -.3141149 _cons | -22.17173 6.13055 -3.62 0.000 -34.18739 -10.15607 -------------+---------------------------------------------------------------- /lndelta | -1.255314 .2418491 -1.72933 -.7812984 -------------+---------------------------------------------------------------- delta | .2849863 .0689237 .1774033 .4578112 ------------------------------------------------------------------------------ Likelihood-ratio test of delta=0: chibar2(01) = 24.08 Prob>=chibar2 = 0.000 . * just for completeness, estimate a poisson ; . * with fips and year effects; . poisson mc_deaths1630 `xlist1'; Iteration 0: log likelihood = -12619.428 Iteration 1: log likelihood = -4528.7595 Iteration 2: log likelihood = -2136.3574 Iteration 3: log likelihood = -2019.4384 Iteration 4: log likelihood = -2018.7586 Iteration 5: log likelihood = -2018.7586 Poisson regression Number of obs = 714 LR chi2(66) = 14390.82 Prob > chi2 = 0.0000 Log likelihood = -2018.7586 Pseudo R2 = 0.7809 ------------------------------------------------------------------------------ mc_deat~1630 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _Ifips_2 | -2.013471 .4316742 -4.66 0.000 -2.859537 -1.167405 _Ifips_4 | -.0073744 .0894577 -0.08 0.934 -.1827082 .1679594 _Ifips_5 | -.3797257 .1628001 -2.33 0.020 -.6988081 -.0606433 _Ifips_6 | .4220235 .4250985 0.99 0.321 -.4111543 1.255201 _Ifips_8 | -.6714285 .1473467 -4.56 0.000 -.9602227 -.3826343 _Ifips_9 | -1.09277 .2553629 -4.28 0.000 -1.593272 -.5922677 _Ifips_10 | -1.540808 .388243 -3.97 0.000 -2.30175 -.7798658 _Ifips_11 | -1.869823 .4673514 -4.00 0.000 -2.785815 -.953831 _Ifips_12 | .6061712 .2449328 2.47 0.013 .1261118 1.086231 _Ifips_13 | -.005155 .1583715 -0.03 0.974 -.3155575 .3052474 _Ifips_15 | -.9847222 .2849075 -3.46 0.001 -1.543131 -.4263139 _Ifips_16 | -.9785205 .2920755 -3.35 0.001 -1.550978 -.4060631 _Ifips_17 | -.2357851 .2414422 -0.98 0.329 -.7090031 .2374329 _Ifips_18 | -.1552494 .1108709 -1.40 0.161 -.3725523 .0620536 _Ifips_19 | -.6383691 .1463708 -4.36 0.000 -.9252506 -.3514876 _Ifips_20 | -.86203 .1613005 -5.34 0.000 -1.178173 -.5458867 _Ifips_21 | -.2356541 .0983761 -2.40 0.017 -.4284677 -.0428406 _Ifips_22 | -.2028236 .0950827 -2.13 0.033 -.3891823 -.0164649 _Ifips_23 | -.8028741 .2820224 -2.85 0.004 -1.355628 -.2501203 _Ifips_24 | -.6419202 .1847259 -3.47 0.001 -1.003976 -.2798642 _Ifips_25 | -.8549488 .2160991 -3.96 0.000 -1.278495 -.4314023 _Ifips_26 | -.1625749 .196022 -0.83 0.407 -.546771 .2216211 _Ifips_27 | -1.051565 .1489057 -7.06 0.000 -1.343415 -.7597154 _Ifips_28 | -.2986975 .158892 -1.88 0.060 -.6101202 .0127252 _Ifips_29 | -.3059807 .1130244 -2.71 0.007 -.5275044 -.084457 _Ifips_30 | -.8131302 .3621397 -2.25 0.025 -1.522911 -.1033495 _Ifips_31 | -1.363793 .2536301 -5.38 0.000 -1.860899 -.8666869 _Ifips_32 | -.8161817 .236029 -3.46 0.001 -1.27879 -.3535733 _Ifips_33 | -1.248029 .3095416 -4.03 0.000 -1.85472 -.6413391 _Ifips_34 | -.7589203 .2467007 -3.08 0.002 -1.242445 -.2753958 _Ifips_35 | -.3810535 .2203923 -1.73 0.084 -.8130145 .0509075 _Ifips_36 | -.1042365 .3346508 -0.31 0.755 -.7601399 .5516669 _Ifips_37 | .3762338 .1444866 2.60 0.009 .0930452 .6594223 _Ifips_38 | -1.493129 .4217577 -3.54 0.000 -2.319759 -.6664993 _Ifips_39 | -.0137941 .2018076 -0.07 0.946 -.4093297 .3817414 _Ifips_40 | -.4041472 .1167882 -3.46 0.001 -.6330479 -.1752464 _Ifips_41 | -.7149754 .1398886 -5.11 0.000 -.9891521 -.4407987 _Ifips_42 | .178225 .2204041 0.81 0.419 -.2537591 .610209 _Ifips_44 | -1.609483 .3319989 -4.85 0.000 -2.260189 -.9587773 _Ifips_45 | .2308604 .0909002 2.54 0.011 .0526992 .4090216 _Ifips_46 | -1.312744 .3954581 -3.32 0.001 -2.087827 -.5376601 _Ifips_47 | .1808543 .1012694 1.79 0.074 -.0176302 .3793387 _Ifips_48 | .355 .3118993 1.14 0.255 -.2563113 .9663114 _Ifips_49 | -.5841695 .1749509 -3.34 0.001 -.9270671 -.241272 _Ifips_50 | -1.075375 .4247041 -2.53 0.011 -1.90778 -.2429705 _Ifips_51 | -.6288361 .1760808 -3.57 0.000 -.9739481 -.2837242 _Ifips_53 | -.6364704 .1550804 -4.10 0.000 -.9404224 -.3325185 _Ifips_54 | -.0558937 .2142431 -0.26 0.794 -.4758025 .3640152 _Ifips_55 | -.4290023 .1142803 -3.75 0.000 -.6529876 -.205017 _Ifips_56 | -1.781662 .4889227 -3.64 0.000 -2.739933 -.8233908 _Iyear_1992 | -.2628832 .0384162 -6.84 0.000 -.3381775 -.1875889 _Iyear_1993 | -.2081264 .038693 -5.38 0.000 -.2839633 -.1322896 _Iyear_1994 | -.3357597 .0414838 -8.09 0.000 -.4170665 -.2544529 _Iyear_1995 | -.4129979 .0442316 -9.34 0.000 -.4996903 -.3263055 _Iyear_1996 | -.5798579 .0496996 -11.67 0.000 -.6772673 -.4824485 _Iyear_1997 | -.7194088 .0575535 -12.50 0.000 -.8322116 -.6066059 _Iyear_1998 | -.7829745 .0720463 -10.87 0.000 -.9241827 -.6417662 _Iyear_1999 | -.8179211 .0782733 -10.45 0.000 -.971334 -.6645083 _Iyear_2000 | -.8199417 .0896638 -9.14 0.000 -.9956795 -.6442038 _Iyear_2001 | -.6859323 .08771 -7.82 0.000 -.8578407 -.5140239 _Iyear_2002 | -.7571016 .0853388 -8.87 0.000 -.9243626 -.5898407 _Iyear_2003 | -.6558562 .084304 -7.78 0.000 -.821089 -.4906234 _Iyear_2004 | -.642001 .0946942 -6.78 0.000 -.8275982 -.4564037 pci_rl | 1.931553 .471095 4.10 0.000 1.008224 2.854883 pop1630l | .4711974 .1919719 2.45 0.014 .0949394 .8474554 mc_helmet_~w | -.3869036 .0321337 -12.04 0.000 -.4498845 -.3239226 _cons | -22.43245 5.427982 -4.13 0.000 -33.0711 -11.7938 ------------------------------------------------------------------------------ . * on shortcoming of the conditional fixed effects and; . * negative binomial models is they canot exploit; . * correlation in observations within a cluster. for; . * mle models, within group correlation is estimated using a; . * procedure suggested by liang and zeger; . nbreg mc_deaths1630 `xlist1', dispersion(constant) cluster(fips); Fitting Poisson model: Iteration 0: log pseudolikelihood = -12619.428 Iteration 1: log pseudolikelihood = -4528.7595 Iteration 2: log pseudolikelihood = -2136.3574 Iteration 3: log pseudolikelihood = -2019.4384 Iteration 4: log pseudolikelihood = -2018.7586 Iteration 5: log pseudolikelihood = -2018.7586 Fitting constant-only model: Iteration 0: log pseudolikelihood = -5386.246 Iteration 1: log pseudolikelihood = -3534.2051 Iteration 2: log pseudolikelihood = -2942.1067 Iteration 3: log pseudolikelihood = -2929.4485 Iteration 4: log pseudolikelihood = -2929.3789 Iteration 5: log pseudolikelihood = -2929.3789 Fitting full model: Iteration 0: log pseudolikelihood = -2929.3789 (not concave) Iteration 1: log pseudolikelihood = -2861.6637 (not concave) Iteration 2: log pseudolikelihood = -2769.2279 (not concave) Iteration 3: log pseudolikelihood = -2519.7433 (not concave) Iteration 4: log pseudolikelihood = -2231.0544 Iteration 5: log pseudolikelihood = -2075.6852 Iteration 6: log pseudolikelihood = -2012.2648 Iteration 7: log pseudolikelihood = -2006.7975 Iteration 8: log pseudolikelihood = -2006.7183 Iteration 9: log pseudolikelihood = -2006.7183 Negative binomial regression Number of obs = 714 Dispersion = constant Wald chi2(15) = . Log pseudolikelihood = -2006.7183 Prob > chi2 = . (Std. Err. adjusted for 51 clusters in fips) ------------------------------------------------------------------------------ | Robust mc_deat~1630 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _Ifips_2 | -1.995348 .62337 -3.20 0.001 -3.217131 -.7735651 _Ifips_4 | -.0067781 .0817338 -0.08 0.934 -.1669733 .1534172 _Ifips_5 | -.3806699 .180437 -2.11 0.035 -.73432 -.0270199 _Ifips_6 | .4150221 .5962733 0.70 0.486 -.7536521 1.583696 _Ifips_8 | -.6629331 .1751014 -3.79 0.000 -1.006126 -.3197407 _Ifips_9 | -1.07746 .3451937 -3.12 0.002 -1.754027 -.4008927 _Ifips_10 | -1.507366 .5745999 -2.62 0.009 -2.633561 -.3811708 _Ifips_11 | -1.851702 .689824 -2.68 0.007 -3.203732 -.4996719 _Ifips_12 | .6022014 .3284521 1.83 0.067 -.0415529 1.245956 _Ifips_13 | -.0060987 .1872668 -0.03 0.974 -.3731348 .3609375 _Ifips_15 | -.9746018 .4265175 -2.29 0.022 -1.810561 -.138643 _Ifips_16 | -.9841772 .4026478 -2.44 0.015 -1.773352 -.1950021 _Ifips_17 | -.2351275 .3072801 -0.77 0.444 -.8373854 .3671304 _Ifips_18 | -.1552345 .1158193 -1.34 0.180 -.3822361 .0717671 _Ifips_19 | -.6310025 .187704 -3.36 0.001 -.9988956 -.2631094 _Ifips_20 | -.856375 .2104887 -4.07 0.000 -1.268925 -.4438247 _Ifips_21 | -.2387803 .0551065 -4.33 0.000 -.3467871 -.1307735 _Ifips_22 | -.2174301 .0824556 -2.64 0.008 -.37904 -.0558201 _Ifips_23 | -.7907728 .4064604 -1.95 0.052 -1.587421 .005875 _Ifips_24 | -.6381521 .2040353 -3.13 0.002 -1.038054 -.2382502 _Ifips_25 | -.8447458 .2417215 -3.49 0.000 -1.318511 -.3709804 _Ifips_26 | -.1649515 .2409897 -0.68 0.494 -.6372827 .3073797 _Ifips_27 | -1.042823 .1614958 -6.46 0.000 -1.359349 -.7262974 _Ifips_28 | -.3034165 .1407805 -2.16 0.031 -.5793413 -.0274918 _Ifips_29 | -.3050951 .0818453 -3.73 0.000 -.4655091 -.1446812 _Ifips_30 | -.801726 .5141547 -1.56 0.119 -1.809451 .2059986 _Ifips_31 | -1.34903 .3137576 -4.30 0.000 -1.963984 -.7340766 _Ifips_32 | -.799535 .3231929 -2.47 0.013 -1.432982 -.1660885 _Ifips_33 | -1.220286 .4537993 -2.69 0.007 -2.109716 -.3308552 _Ifips_34 | -.7538896 .284917 -2.65 0.008 -1.312317 -.1954625 _Ifips_35 | -.381562 .2975838 -1.28 0.200 -.9648156 .2016916 _Ifips_36 | -.1030466 .4377961 -0.24 0.814 -.9611113 .7550181 _Ifips_37 | .372149 .1699462 2.19 0.029 .0390606 .7052373 _Ifips_38 | -1.511206 .5900228 -2.56 0.010 -2.667629 -.3547821 _Ifips_39 | -.0171986 .264031 -0.07 0.948 -.5346899 .5002927 _Ifips_40 | -.4051258 .1260134 -3.21 0.001 -.6521076 -.1581441 _Ifips_41 | -.7167952 .1349698 -5.31 0.000 -.9813311 -.4522594 _Ifips_42 | .1759052 .2806829 0.63 0.531 -.3742231 .7260335 _Ifips_44 | -1.585095 .4755653 -3.33 0.001 -2.517186 -.6530041 _Ifips_45 | .2302458 .0921781 2.50 0.012 .04958 .4109116 _Ifips_46 | -1.293822 .561773 -2.30 0.021 -2.394876 -.1927668 _Ifips_47 | .1822989 .0741615 2.46 0.014 .036945 .3276528 _Ifips_48 | .3479484 .4419754 0.79 0.431 -.5183075 1.214204 _Ifips_49 | -.5823156 .2176335 -2.68 0.007 -1.008869 -.1557619 _Ifips_50 | -1.052194 .6006607 -1.75 0.080 -2.229467 .1250791 _Ifips_51 | -.6244868 .1892305 -3.30 0.001 -.9953718 -.2536018 _Ifips_53 | -.6334727 .1523563 -4.16 0.000 -.9320855 -.3348598 _Ifips_54 | -.0607456 .2666656 -0.23 0.820 -.5834005 .4619094 _Ifips_55 | -.427415 .1151324 -3.71 0.000 -.6530703 -.2017597 _Ifips_56 | -1.782767 .7016752 -2.54 0.011 -3.158025 -.407509 _Iyear_1992 | -.2553753 .075236 -3.39 0.001 -.4028351 -.1079155 _Iyear_1993 | -.2026962 .057232 -3.54 0.000 -.3148689 -.0905235 _Iyear_1994 | -.3307537 .0595264 -5.56 0.000 -.4474232 -.2140841 _Iyear_1995 | -.4059678 .0655915 -6.19 0.000 -.5345249 -.2774108 _Iyear_1996 | -.570698 .0714907 -7.98 0.000 -.7108172 -.4305787 _Iyear_1997 | -.7116923 .1092382 -6.52 0.000 -.9257953 -.4975893 _Iyear_1998 | -.7741427 .1314492 -5.89 0.000 -1.031778 -.5165069 _Iyear_1999 | -.8088591 .1289684 -6.27 0.000 -1.061632 -.5560857 _Iyear_2000 | -.8113763 .1467253 -5.53 0.000 -1.098953 -.5237999 _Iyear_2001 | -.675779 .1353834 -4.99 0.000 -.9411255 -.4104325 _Iyear_2002 | -.7469265 .1404743 -5.32 0.000 -1.022251 -.471602 _Iyear_2003 | -.6466251 .1435441 -4.50 0.000 -.9279663 -.3652839 _Iyear_2004 | -.6317418 .1457827 -4.33 0.000 -.9174706 -.346013 pci_rl | 1.899044 .6203005 3.06 0.002 .6832769 3.11481 pop1630l | .4759465 .291388 1.63 0.102 -.0951636 1.047056 mc_helmet_~w | -.3856393 .0833271 -4.63 0.000 -.5489573 -.2223212 _cons | -22.17173 6.673072 -3.32 0.001 -35.25071 -9.09275 -------------+---------------------------------------------------------------- /lndelta | -1.255314 .2909652 -1.825595 -.6850327 -------------+---------------------------------------------------------------- delta | .2849863 .0829211 .1611217 .5040737 ------------------------------------------------------------------------------ . log close; log: c:\bill\spring2011\helmet_law_data.log log type: text closed on: 5 Apr 2011, 08:22:06 -------------------------------------------------------------------------------