fit.1<-glm(PCT_NON_MEDICAL_REFUSAL~PCT_BELOW_POV+TOTAL_POP+PCT_BA_OR_MORE+PCT_WHITE,data=schools_county,family=poisson)
summary(fit.1)
##
## Call:
## glm(formula = PCT_NON_MEDICAL_REFUSAL ~ PCT_BELOW_POV + TOTAL_POP +
## PCT_BA_OR_MORE + PCT_WHITE, family = poisson, data = schools_county)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3907 -1.0272 -0.3213 0.4192 4.0727
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.820e-01 1.133e+00 0.249 0.8035
## PCT_BELOW_POV -3.561e-02 2.276e-02 -1.565 0.1176
## TOTAL_POP -1.799e-08 2.611e-07 -0.069 0.9451
## PCT_BA_OR_MORE 7.447e-02 3.533e-02 2.108 0.0350 *
## PCT_WHITE 1.950e-02 1.135e-02 1.719 0.0857 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 92.883 on 38 degrees of freedom
## Residual deviance: 79.776 on 34 degrees of freedom
## AIC: Inf
##
## Number of Fisher Scoring iterations: 5
fit.2<-glm(PCT_NON_MEDICAL_REFUSAL~PCT_BELOW_POV+TOTAL_POP+PCT_BA_OR_MORE+PCT_WHITE+BELOW_18_PCT_POV,data=schools_county,family=poisson)
summary(fit.2)
##
## Call:
## glm(formula = PCT_NON_MEDICAL_REFUSAL ~ PCT_BELOW_POV + TOTAL_POP +
## PCT_BA_OR_MORE + PCT_WHITE + BELOW_18_PCT_POV, family = poisson,
## data = schools_county)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2858 -1.0136 -0.0473 0.3718 3.9984
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.755e-02 1.195e+00 -0.031 0.9749
## PCT_BELOW_POV -4.695e-02 2.674e-02 -1.756 0.0791 .
## TOTAL_POP 6.379e-08 2.737e-07 0.233 0.8157
## PCT_BA_OR_MORE 8.107e-02 3.579e-02 2.265 0.0235 *
## PCT_WHITE 2.070e-02 1.143e-02 1.811 0.0701 .
## BELOW_18_PCT_POV 1.669e-02 1.872e-02 0.892 0.3725
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 92.883 on 38 degrees of freedom
## Residual deviance: 78.966 on 33 degrees of freedom
## AIC: Inf
##
## Number of Fisher Scoring iterations: 5
fit.3<-glm(PCT_NON_MEDICAL_REFUSAL~PCT_BELOW_POV+TOTAL_POP+PCT_BA_OR_MORE+PCT_WHITE+BELOW_18_PCT_POV+PCT_FEMALE,data=schools_county,family=poisson)
summary(fit.3)
##
## Call:
## glm(formula = PCT_NON_MEDICAL_REFUSAL ~ PCT_BELOW_POV + TOTAL_POP +
## PCT_BA_OR_MORE + PCT_WHITE + BELOW_18_PCT_POV + PCT_FEMALE,
## family = poisson, data = schools_county)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.6586 -0.9812 -0.0657 0.4483 3.5801
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -5.536e+00 4.390e+00 -1.261 0.2073
## PCT_BELOW_POV -3.485e-02 2.796e-02 -1.246 0.2127
## TOTAL_POP 3.435e-08 2.760e-07 0.124 0.9010
## PCT_BA_OR_MORE 7.110e-02 3.646e-02 1.950 0.0512 .
## PCT_WHITE 1.610e-02 1.204e-02 1.337 0.1811
## BELOW_18_PCT_POV 1.784e-02 1.872e-02 0.953 0.3408
## PCT_FEMALE 1.148e-01 8.824e-02 1.300 0.1934
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 92.883 on 38 degrees of freedom
## Residual deviance: 77.255 on 32 degrees of freedom
## AIC: Inf
##
## Number of Fisher Scoring iterations: 5
aic<-round(c(
fit.1$deviance+2*length(fit.1$coefficients),
fit.2$deviance+2*length(fit.2$coefficients),
fit.3$deviance+2*length(fit.3$coefficients)),2)
aic_table<-as.data.frame(aic)
schools_summary<-schools %>% dplyr::summarize(n_students=sum(K_12_enrollment),mean_vaccine_complete=mean(Percent_complete_for_all_immunizations),mean_refusal=mean(Percent_with_any_exemption))
schools_summary
## n_students mean_vaccine_complete mean_refusal
## 1 1129795 85.35069 6.413801
plot(schools_county$PCT_NON_MEDICAL_REFUSAL,schools_county$PCT_BA_OR_MORE)
abline(glm(schools_county$PCT_NON_MEDICAL_REFUSAL~schools_county$PCT_BA_OR_MORE))
stargazer(schools_county,type="html")
|
|
|
Statistic
|
N
|
Mean
|
St. Dev.
|
Min
|
Pctl(25)
|
Pctl(75)
|
Max
|
|
|
|
PCT_COMPLETE_ALL_IMMUNIZATION
|
39
|
83.525
|
8.500
|
50.127
|
79.945
|
88.978
|
96.233
|
|
PCT_ANY_EXEMPTION
|
39
|
7.251
|
4.606
|
1.689
|
4.308
|
8.739
|
23.813
|
|
PCT_NON_MEDICAL_REFUSAL
|
39
|
6.240
|
4.271
|
1.244
|
3.334
|
7.329
|
22.780
|
|
PCT_UNDERVACCINATED
|
39
|
9.224
|
4.889
|
0.400
|
5.973
|
12.015
|
26.060
|
|
PCT_BELOW_POV
|
39
|
15.649
|
4.286
|
9
|
12.6
|
16.9
|
30
|
|
BELOW_18_PCT_POV
|
39
|
20.454
|
4.949
|
11.700
|
17.300
|
23.000
|
31.300
|
|
TOTAL_POP
|
39
|
181,362.700
|
366,978.800
|
2,231
|
20,836.5
|
153,997
|
2,079,550
|
|
PCT_LESS_HS_GRAD
|
39
|
23.744
|
4.686
|
14.900
|
20.150
|
26.650
|
35.300
|
|
PCT_HS_GRAD
|
39
|
14.326
|
3.153
|
9.200
|
12.200
|
15.800
|
24.500
|
|
PCT_SOME_COLLEGE
|
39
|
11.544
|
2.964
|
7.400
|
9.400
|
13.350
|
18.900
|
|
PCT_BA_OR_MORE
|
39
|
5.764
|
2.344
|
2.800
|
4.200
|
6.500
|
14.300
|
|
PCT_WHITE
|
39
|
84.685
|
7.866
|
67.200
|
79.400
|
90.850
|
95.600
|
|
PCT_BLACK
|
39
|
1.349
|
1.447
|
0.000
|
0.500
|
1.800
|
6.700
|
|
PCT_NATIVE_AM
|
39
|
2.292
|
2.814
|
0.300
|
0.900
|
2.600
|
15.500
|
|
PCT_ASIAN
|
39
|
2.603
|
3.038
|
0.600
|
0.900
|
2.300
|
16.000
|
|
PCT_PACIFIC_ISLANDER
|
39
|
0.300
|
0.313
|
0.000
|
0.100
|
0.350
|
1.400
|
|
PCT_OTHER_RACE
|
39
|
4.826
|
6.576
|
0.000
|
1.000
|
3.950
|
23.700
|
|
PCT_TWO_OR_MORE_RACES
|
39
|
3.944
|
1.381
|
1.500
|
3.100
|
4.600
|
7.500
|
|
PCT_HISPANIC_ANY_RACE
|
39
|
13.744
|
14.319
|
3.000
|
5.700
|
14.850
|
61.900
|
|
PCT_AGE_5below
|
39
|
5.887
|
1.591
|
2.900
|
4.900
|
6.450
|
10.800
|
|
PCT_AGE_5-9
|
39
|
6.041
|
1.573
|
2.800
|
5.250
|
6.500
|
10.700
|
|
PCT_AGE_10-14
|
39
|
6.210
|
1.212
|
3.600
|
5.600
|
6.850
|
9.500
|
|
PCT_AGE_15-19
|
39
|
6.487
|
1.702
|
4.000
|
5.650
|
6.750
|
14.900
|
|
PCT_AGE_20-24
|
39
|
6.674
|
3.725
|
1
|
5.2
|
7.0
|
24
|
|
PCT_AGE_25-34
|
39
|
11.449
|
2.473
|
6.300
|
9.600
|
12.950
|
17.000
|
|
PCT_AGE_35-44
|
39
|
11.156
|
1.475
|
8.200
|
10.300
|
11.900
|
14.900
|
|
PCT_AGE_45-54
|
39
|
12.641
|
1.311
|
8.200
|
11.900
|
13.400
|
15.600
|
|
PCT_AGE_55-59
|
39
|
7.500
|
1.485
|
4.600
|
6.550
|
8.500
|
11.600
|
|
PCT_AGE_60-64
|
39
|
7.318
|
1.837
|
4.100
|
6.100
|
8.700
|
11.600
|
|
PCT_AGE_65-74
|
39
|
11.228
|
3.899
|
5.000
|
8.550
|
13.500
|
20.400
|
|
PCT_AGE_75-84
|
39
|
5.210
|
1.664
|
2.300
|
3.750
|
6.050
|
8.700
|
|
PCT_85plus
|
39
|
2.195
|
0.765
|
0.800
|
1.700
|
2.700
|
4.400
|
|
PCT_MALE
|
39
|
50.018
|
0.894
|
48.100
|
49.400
|
50.600
|
52.100
|
|
PCT_FEMALE
|
39
|
49.982
|
0.894
|
47.900
|
49.400
|
50.600
|
51.900
|
|
|