Model 1 (no interations)
m1 = glm(MedHxMarijStatusCurrent~Sex + Race + Age0 + PovStat,data=exdata,family=binomial)
summary(m1)
##
## Call:
## glm(formula = MedHxMarijStatusCurrent ~ Sex + Race + Age0 + PovStat,
## family = binomial, data = exdata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.941 -0.560 -0.449 -0.349 2.575
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.5812 0.3155 -1.84 0.065
## SexMen 0.6785 0.1175 5.77 7.7e-09
## RaceAfrAm 0.5632 0.1260 4.47 7.8e-06
## Age0 -0.0450 0.0064 -7.02 2.2e-12
## PovStatBelow 0.1041 0.1191 0.87 0.382
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 2114.1 on 2800 degrees of freedom
## Residual deviance: 2006.3 on 2796 degrees of freedom
## (1 observation deleted due to missingness)
## AIC: 2016
##
## Number of Fisher Scoring iterations: 5
OR for Model 1
exp(cbind(OR = coef(m1), confint(m1)))
## Waiting for profiling to be done...
## OR 2.5 % 97.5 %
## (Intercept) 0.5592 0.3004 1.035
## SexMen 1.9710 1.5669 2.485
## RaceAfrAm 1.7563 1.3757 2.255
## Age0 0.9560 0.9440 0.968
## PovStatBelow 1.1097 0.8780 1.401
Model 2 (two-way interations)
m2 = glm(MedHxMarijStatusCurrent~(Sex + Race + Age0 + PovStat)^2,data=exdata,family=binomial)
summary(m2)
##
## Call:
## glm(formula = MedHxMarijStatusCurrent ~ (Sex + Race + Age0 +
## PovStat)^2, family = binomial, data = exdata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.948 -0.558 -0.449 -0.346 2.576
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.29847 0.64992 -0.46 0.6461
## SexMen 1.03475 0.61694 1.68 0.0935
## RaceAfrAm -0.31275 0.66795 -0.47 0.6396
## Age0 -0.04971 0.01404 -3.54 0.0004
## PovStatBelow 0.12109 0.63711 0.19 0.8493
## SexMen:RaceAfrAm 0.16506 0.25700 0.64 0.5207
## SexMen:Age0 -0.00896 0.01290 -0.69 0.4875
## SexMen:PovStatBelow -0.14262 0.24118 -0.59 0.5543
## RaceAfrAm:Age0 0.01565 0.01395 1.12 0.2621
## RaceAfrAm:PovStatBelow 0.21673 0.26593 0.82 0.4151
## Age0:PovStatBelow -0.00199 0.01320 -0.15 0.8801
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 2114.1 on 2800 degrees of freedom
## Residual deviance: 2003.5 on 2790 degrees of freedom
## (1 observation deleted due to missingness)
## AIC: 2025
##
## Number of Fisher Scoring iterations: 5
OR for Model 2
exp(cbind(OR = coef(m2), confint(m2)))
## Waiting for profiling to be done...
## OR 2.5 % 97.5 %
## (Intercept) 0.7420 0.2043 2.6212
## SexMen 2.8144 0.8421 9.4731
## RaceAfrAm 0.7314 0.1968 2.7064
## Age0 0.9515 0.9254 0.9778
## PovStatBelow 1.1287 0.3222 3.9255
## SexMen:RaceAfrAm 1.1795 0.7119 1.9524
## SexMen:Age0 0.9911 0.9663 1.0165
## SexMen:PovStatBelow 0.8671 0.5396 1.3902
## RaceAfrAm:Age0 1.0158 0.9885 1.0441
## RaceAfrAm:PovStatBelow 1.2420 0.7421 2.1086
## Age0:PovStatBelow 0.9980 0.9724 1.0241
Model 1 (no interations)
m1 = glm(MedHxMarijStatusCurrent~Sex + Age0 + PovStat,data=WhiteCB,family=binomial)
summary(m1)
##
## Call:
## glm(formula = MedHxMarijStatusCurrent ~ Sex + Age0 + PovStat,
## family = binomial, data = WhiteCB)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.760 -0.478 -0.384 -0.304 2.614
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.0292 0.5277 -0.06 0.9559
## SexMen 0.5929 0.2067 2.87 0.0041
## Age0 -0.0552 0.0113 -4.88 1.1e-06
## PovStatBelow -0.0401 0.2228 -0.18 0.8572
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 723.24 on 1184 degrees of freedom
## Residual deviance: 690.32 on 1181 degrees of freedom
## AIC: 698.3
##
## Number of Fisher Scoring iterations: 5
OR for Model 1
exp(cbind(OR = coef(m1), confint(m1)))
## Waiting for profiling to be done...
## OR 2.5 % 97.5 %
## (Intercept) 0.9712 0.3432 2.7255
## SexMen 1.8092 1.2088 2.7238
## Age0 0.9463 0.9252 0.9673
## PovStatBelow 0.9607 0.6141 1.4749
Model 2 (two-way interations)
m2 = glm(MedHxMarijStatusCurrent~(Sex + Age0 + PovStat)^2,data=WhiteCB,family=binomial)
summary(m2)
##
## Call:
## glm(formula = MedHxMarijStatusCurrent ~ (Sex + Age0 + PovStat)^2,
## family = binomial, data = WhiteCB)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.959 -0.448 -0.379 -0.322 2.601
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.3511 0.8612 -1.57 0.117
## SexMen 2.5217 1.0630 2.37 0.018
## Age0 -0.0249 0.0182 -1.37 0.170
## PovStatBelow 0.8324 1.1826 0.70 0.482
## SexMen:Age0 -0.0448 0.0229 -1.96 0.050
## SexMen:PovStatBelow 0.2168 0.4536 0.48 0.633
## Age0:PovStatBelow -0.0222 0.0253 -0.88 0.380
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 723.24 on 1184 degrees of freedom
## Residual deviance: 685.45 on 1178 degrees of freedom
## AIC: 699.4
##
## Number of Fisher Scoring iterations: 5
OR for Model 2
exp(cbind(OR = coef(m2), confint(m2)))
## Waiting for profiling to be done...
## OR 2.5 % 97.5 %
## (Intercept) 0.2590 0.04587 1.3606
## SexMen 12.4500 1.57338 102.4143
## Age0 0.9754 0.94093 1.0107
## PovStatBelow 2.2988 0.22543 23.6178
## SexMen:Age0 0.9562 0.91391 0.9999
## SexMen:PovStatBelow 1.2421 0.50880 3.0360
## Age0:PovStatBelow 0.9780 0.92980 1.0271
Model 1 (African American Only - no interations)
m1 = glm(MedHxMarijStatusCurrent~Sex + Age0 + PovStat,data=AfrAmCB,family=binomial)
summary(m1)
##
## Call:
## glm(formula = MedHxMarijStatusCurrent ~ Sex + Age0 + PovStat,
## family = binomial, data = AfrAmCB)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.930 -0.615 -0.509 -0.391 2.413
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.30193 0.38019 -0.79 0.43
## SexMen 0.71746 0.14280 5.02 5.1e-07
## Age0 -0.03989 0.00778 -5.12 3.0e-07
## PovStatBelow 0.16663 0.14203 1.17 0.24
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1368.3 on 1615 degrees of freedom
## Residual deviance: 1314.0 on 1612 degrees of freedom
## AIC: 1322
##
## Number of Fisher Scoring iterations: 4
OR for Model 1
exp(cbind(OR = coef(m1), confint(m1)))
## Waiting for profiling to be done...
## OR 2.5 % 97.5 %
## (Intercept) 0.7394 0.3494 1.5529
## SexMen 2.0492 1.5511 2.7164
## Age0 0.9609 0.9463 0.9756
## PovStatBelow 1.1813 0.8942 1.5612
Model 2 (African American Only - two-way interations)
m2 = glm(MedHxMarijStatusCurrent~(Sex + Age0 + PovStat)^2,data=AfrAmCB,family=binomial)
summary(m2)
##
## Call:
## glm(formula = MedHxMarijStatusCurrent ~ (Sex + Age0 + PovStat)^2,
## family = binomial, data = AfrAmCB)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.888 -0.629 -0.518 -0.377 2.501
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.05801 0.66843 -0.09 0.93084
## SexMen 0.51380 0.74854 0.69 0.49246
## Age0 -0.04726 0.01428 -3.31 0.00094
## PovStatBelow 0.04238 0.73792 0.06 0.95420
## SexMen:Age0 0.00786 0.01570 0.50 0.61648
## SexMen:PovStatBelow -0.30213 0.28744 -1.05 0.29321
## Age0:PovStatBelow 0.00641 0.01563 0.41 0.68171
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1368.3 on 1615 degrees of freedom
## Residual deviance: 1312.4 on 1609 degrees of freedom
## AIC: 1326
##
## Number of Fisher Scoring iterations: 5
OR for Model 2
exp(cbind(OR = coef(m2), confint(m2)))
## Waiting for profiling to be done...
## OR 2.5 % 97.5 %
## (Intercept) 0.9436 0.2500 3.4551
## SexMen 1.6716 0.3865 7.2922
## Age0 0.9538 0.9272 0.9807
## PovStatBelow 1.0433 0.2462 4.4556
## SexMen:Age0 1.0079 0.9774 1.0395
## SexMen:PovStatBelow 0.7392 0.4196 1.2965
## Age0:PovStatBelow 1.0064 0.9760 1.0378