ld-archer
commented
1 year ago Minimal
Call:
glm(formula = form.mort.ls, family = binomial(link = "probit"),
data = trans2)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.4192 -0.2913 -0.1587 -0.0902 3.7783
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -4.265387 0.310281 -13.747 < 2e-16 ***
male1 0.242307 0.021970 11.029 < 2e-16 ***
white 0.230107 0.069787 3.297 0.000976 ***
hsless1 0.085600 0.023272 3.678 0.000235 ***
college1 -0.026129 0.039422 -0.663 0.507452
l2age65l 0.038887 0.005140 7.566 3.85e-14 ***
l2age6574 0.042725 0.004040 10.576 < 2e-16 ***
l2age75p 0.053390 0.002293 23.284 < 2e-16 ***
l2lnly1 -0.883458 0.030147 -29.305 < 2e-16 ***
l2lnly2 -0.772954 0.035671 -21.669 < 2e-16 ***
l2lnly3 -0.570262 0.061293 -9.304 < 2e-16 ***
l2sociso1 -0.227997 0.036719 -6.209 5.32e-10 ***
l2sociso2 -0.154433 0.033502 -4.610 4.03e-06 ***
l2sociso3 -0.051948 0.039794 -1.305 0.191752
l2sociso4 -0.015867 0.044090 -0.360 0.718935
l2sociso5 0.042965 0.062694 0.685 0.493140
l2sociso6 0.221230 0.166625 1.328 0.184274
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 21723 on 54011 degrees of freedom
Residual deviance: 16242 on 53995 degrees of freedom
(5657 observations deleted due to missingness)
AIC: 16276
Number of Fisher Scoring iterations: 7Final
Call:
glm(formula = form.mort.test, family = binomial(link = "probit"),
data = trans2)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.6907 -0.2426 -0.1319 -0.0783 3.8889
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.928007 0.395789 -9.924 < 2e-16 ***
male1 0.256070 0.027044 9.469 < 2e-16 ***
white 0.199304 0.090253 2.208 0.027224 *
hsless1 0.056567 0.027749 2.039 0.041500 *
college1 0.009276 0.046181 0.201 0.840800
l2age65l 0.029290 0.005934 4.936 7.97e-07 ***
l2age6574 0.030629 0.004810 6.368 1.91e-10 ***
l2age75p 0.052990 0.002873 18.443 < 2e-16 ***
l2lnly1 -0.660823 0.033983 -19.446 < 2e-16 ***
l2lnly2 -0.584526 0.038524 -15.173 < 2e-16 ***
l2sociso1 -0.285226 0.170916 -1.669 0.095155 .
l2sociso2 -0.189557 0.169426 -1.119 0.263219
l2sociso3 -0.128757 0.169849 -0.758 0.448411
l2sociso4 -0.095824 0.170748 -0.561 0.574660
l2sociso5 -0.068575 0.176403 -0.389 0.697467
l2cancre 0.525151 0.035226 14.908 < 2e-16 ***
l2diabe 0.134391 0.037594 3.575 0.000350 ***
l2hearte 0.299084 0.027658 10.814 < 2e-16 ***
l2demene 0.462141 0.070762 6.531 6.54e-11 ***
l2lunge 0.394924 0.038790 10.181 < 2e-16 ***
l2stroke 0.177838 0.042637 4.171 3.03e-05 ***
l2smokev 0.092029 0.030093 3.058 0.002227 **
l2smoken 0.184679 0.049238 3.751 0.000176 ***
l2smokef 0.001006 0.003064 0.328 0.742762
l2alcfreq1 -0.142315 0.045986 -3.095 0.001970 **
l2alcfreq2 -0.295976 0.086753 -3.412 0.000646 ***
l2alcfreq3 -0.224907 0.062297 -3.610 0.000306 ***
l2alcfreq5 -0.205366 0.057237 -3.588 0.000333 ***
l2alcfreq6 -0.140310 0.065326 -2.148 0.031726 *
l2alcfreq7 -0.075171 0.053812 -1.397 0.162435
l2alcfreq8 -0.034031 0.045667 -0.745 0.456141
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 15390 on 47820 degrees of freedom
Residual deviance: 11409 on 47790 degrees of freedom
(11848 observations deleted due to missingness)
AIC: 11471
Number of Fisher Scoring iterations: 7
Currently chronic diseases and functional limitations have been removed from the mortality model to focus on loneliness and social isolation. I need to add these back and make sure nothing breaks the good work I've just done.