library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(janitor)
##
## Attaching package: 'janitor'
## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.test
library(haven)
library(readr)
library(ggplot2)
library(sur)
library(scales)
##
## Attaching package: 'scales'
## The following object is masked from 'package:readr':
##
## col_factor
anes2020<-read_dta("C:\\Users\\Bryan\\Downloads\\anes2020.dta")
anes2020 %>%
tabyl(V202186)
## V202186 n percent
## -9 67 0.0080917874
## -7 77 0.0092995169
## -6 750 0.0905797101
## -5 16 0.0019323671
## 0 457 0.0551932367
## 1 5 0.0006038647
## 2 2 0.0002415459
## 3 1 0.0001207729
## 4 3 0.0003623188
## 5 23 0.0027777778
## 6 4 0.0004830918
## 7 1 0.0001207729
## 8 2 0.0002415459
## 9 1 0.0001207729
## 10 40 0.0048309179
## 11 1 0.0001207729
## 12 1 0.0001207729
## 15 276 0.0333333333
## 16 1 0.0001207729
## 20 36 0.0043478261
## 23 1 0.0001207729
## 25 25 0.0030193237
## 26 1 0.0001207729
## 30 288 0.0347826087
## 31 1 0.0001207729
## 32 1 0.0001207729
## 33 1 0.0001207729
## 35 12 0.0014492754
## 40 408 0.0492753623
## 42 1 0.0001207729
## 45 38 0.0045893720
## 46 1 0.0001207729
## 48 3 0.0003623188
## 49 1 0.0001207729
## 50 1081 0.1305555556
## 51 2 0.0002415459
## 52 1 0.0001207729
## 54 1 0.0001207729
## 55 23 0.0027777778
## 56 1 0.0001207729
## 57 1 0.0001207729
## 58 2 0.0002415459
## 59 2 0.0002415459
## 60 643 0.0776570048
## 65 65 0.0078502415
## 66 1 0.0001207729
## 68 1 0.0001207729
## 69 3 0.0003623188
## 70 912 0.1101449275
## 75 134 0.0161835749
## 76 3 0.0003623188
## 77 1 0.0001207729
## 78 1 0.0001207729
## 80 181 0.0218599034
## 84 2 0.0002415459
## 85 1061 0.1281400966
## 86 6 0.0007246377
## 87 3 0.0003623188
## 88 6 0.0007246377
## 89 2 0.0002415459
## 90 181 0.0218599034
## 92 2 0.0002415459
## 95 58 0.0070048309
## 96 1 0.0001207729
## 97 1 0.0001207729
## 98 4 0.0004830918
## 99 4 0.0004830918
## 100 851 0.1027777778
## 998 3 0.0003623188
## 999 490 0.0591787440
anes2020 %>%
tabyl(V201600)
## V201600 n percent
## -9 67 0.008091787
## 1 3763 0.454468599
## 2 4450 0.537439614
anes2020 %>%
tabyl(V201507x)
## V201507x n percent
## -9 354 0.042753623
## 18 34 0.004106280
## 19 49 0.005917874
## 20 45 0.005434783
## 21 52 0.006280193
## 22 57 0.006884058
## 23 74 0.008937198
## 24 92 0.011111111
## 25 107 0.012922705
## 26 107 0.012922705
## 27 135 0.016304348
## 28 119 0.014371981
## 29 130 0.015700483
## 30 142 0.017149758
## 31 112 0.013526570
## 32 117 0.014130435
## 33 125 0.015096618
## 34 141 0.017028986
## 35 151 0.018236715
## 36 141 0.017028986
## 37 148 0.017874396
## 38 152 0.018357488
## 39 149 0.017995169
## 40 141 0.017028986
## 41 150 0.018115942
## 42 114 0.013768116
## 43 116 0.014009662
## 44 113 0.013647343
## 45 118 0.014251208
## 46 119 0.014371981
## 47 106 0.012801932
## 48 106 0.012801932
## 49 125 0.015096618
## 50 152 0.018357488
## 51 126 0.015217391
## 52 115 0.013888889
## 53 118 0.014251208
## 54 122 0.014734300
## 55 138 0.016666667
## 56 127 0.015338164
## 57 135 0.016304348
## 58 145 0.017512077
## 59 151 0.018236715
## 60 170 0.020531401
## 61 139 0.016787440
## 62 156 0.018840580
## 63 154 0.018599034
## 64 157 0.018961353
## 65 178 0.021497585
## 66 168 0.020289855
## 67 141 0.017028986
## 68 142 0.017149758
## 69 156 0.018840580
## 70 127 0.015338164
## 71 145 0.017512077
## 72 142 0.017149758
## 73 150 0.018115942
## 74 94 0.011352657
## 75 93 0.011231884
## 76 90 0.010869565
## 77 82 0.009903382
## 78 64 0.007729469
## 79 61 0.007367150
## 80 401 0.048429952
anes2020 %>%
tabyl(V201508)
## V201508 n percent
## -9 55 0.0066425121
## -8 1 0.0001207729
## 1 4315 0.5211352657
## 2 7 0.0008454106
## 3 567 0.0684782609
## 4 1221 0.1474637681
## 5 163 0.0196859903
## 6 1951 0.2356280193
anes2020 %>%
tabyl(V201509)
## V201509 n percent
## -9 6 0.0007246377
## -1 4378 0.5287439614
## 1 745 0.0899758454
## 2 3151 0.3805555556
anes2020 <- filter(anes2020, V202186 >= 0 & V202186 <= 100)
anes2020 <- filter(anes2020, V201600 >= 1)
anes2020 <- filter(anes2020, V201507x >= 18)
anes2020 <- filter(anes2020, V201508 >= 1 & V201508 <= 6)
anes2020 <- filter(anes2020, V201509 >= 1 & V201509 <=2)
anes2020 %>%
ggplot(mapping = aes(V202186))+
geom_histogram()+
ggtitle(label="World Health Organziation Distribution")+
xlab(label="World Health Organziation Feelings")
## Don't know how to automatically pick scale for object of type haven_labelled/vctrs_vctr/double. Defaulting to continuous.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
anes2020 %>%
ggplot(mapping = aes(V202186, stat=..density..))+geom_density()+ggtitle(label="World Health Organziation Feelings Distribution")+xlab(label="World Health Organziation Feelings")
## Don't know how to automatically pick scale for object of type haven_labelled/vctrs_vctr/double. Defaulting to continuous.
qqnorm(anes2020$V202186)
ggplot(anes2020) + geom_point(mapping = aes(x=V201507x, y=V202186))
## Don't know how to automatically pick scale for object of type haven_labelled/vctrs_vctr/double. Defaulting to continuous.
## Don't know how to automatically pick scale for object of type haven_labelled/vctrs_vctr/double. Defaulting to continuous.
scatter.smooth(anes2020$V201507x,anes2020$V202186)
lmAgeWHO = lm(V202186~V201507x, data = anes2020)
summary(lmAgeWHO)
##
## Call:
## lm(formula = V202186 ~ V201507x, data = anes2020)
##
## Residuals:
## Min 1Q Median 3Q Max
## -64.870 -14.564 5.472 20.904 36.246
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 65.19452 1.42953 45.606 <2e-16 ***
## V201507x -0.01801 0.02690 -0.669 0.503
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 27.51 on 3041 degrees of freedom
## Multiple R-squared: 0.0001473, Adjusted R-squared: -0.0001815
## F-statistic: 0.4481 on 1 and 3041 DF, p-value: 0.5033
anes2020 %>%
ggplot(mapping=aes(y=V202186, x=factor(V201600)))+
geom_boxplot()+
ggtitle(label="Distribution of World Health Organization Feelings by Gender") +
xlab(label="World Health Organization")
## Don't know how to automatically pick scale for object of type haven_labelled/vctrs_vctr/double. Defaulting to continuous.
anes2020$gender.f <- factor(anes2020$V201600)
tapply(anes2020$V202186, anes2020$gender.f, mean)
## 1 2
## 60.28822 67.11584
contr.treatment(2)
## 2
## 1 0
## 2 1
contrasts(anes2020$gender.f) = contr.treatment(2)
summary(lm(V202186~gender.f, anes2020))
##
## Call:
## lm(formula = V202186 ~ gender.f, data = anes2020)
##
## Residuals:
## Min 1Q Median 3Q Max
## -67.116 -17.116 2.884 19.712 39.712
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60.2882 0.7706 78.24 < 2e-16 ***
## gender.f2 6.8276 1.0055 6.79 1.34e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 27.31 on 3041 degrees of freedom
## Multiple R-squared: 0.01493, Adjusted R-squared: 0.01461
## F-statistic: 46.1 on 1 and 3041 DF, p-value: 1.343e-11
anes2020$cohab.f <- factor(anes2020$V201509)
contr.treatment(2)
## 2
## 1 0
## 2 1
summary(lm(V202186~cohab.f, anes2020))
##
## Call:
## lm(formula = V202186 ~ cohab.f, data = anes2020)
##
## Residuals:
## Min 1Q Median 3Q Max
## -64.34 -14.34 5.66 20.66 35.88
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 64.1176 1.1445 56.023 <2e-16 ***
## cohab.f2 0.2223 1.2716 0.175 0.861
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 27.52 on 3041 degrees of freedom
## Multiple R-squared: 1.005e-05, Adjusted R-squared: -0.0003188
## F-statistic: 0.03057 on 1 and 3041 DF, p-value: 0.8612
anes2020$relationship_status <-paste(anes2020$V201509, anes2020$V201508, sep = "" )
summary(anes2020$relationship_status)
## Length Class Mode
## 3043 character character
tabyl(anes2020$relationship_status)
## anes2020$relationship_status n percent
## 13 19 0.006243838
## 14 160 0.052579691
## 15 22 0.007229708
## 16 377 0.123890897
## 23 418 0.137364443
## 24 846 0.278015117
## 25 95 0.031219192
## 26 1106 0.363457115
anes2020$relations_coded <-car::Recode(anes2020$ relationship_status, recodes="'13 to 16' = 'Cohabitating'; '23 to 26' = 'Single'; else=NA", as.factor=T)
anes2020 %>%
tabyl(relations_coded)
## relations_coded n percent valid_percent
## <NA> 3043 1 NA
anes2020 %>%
ggplot(mapping=aes(y=V202186,x=factor(relations_coded)))+
geom_boxplot()+
ggtitle(label="World Health Organization Feelings by Relationship Type")+
xlab(label="World Health Organization")
## Don't know how to automatically pick scale for object of type haven_labelled/vctrs_vctr/double. Defaulting to continuous.
lmage = lm(V202186~V201507x, data = anes2020)
summary(lmage)
##
## Call:
## lm(formula = V202186 ~ V201507x, data = anes2020)
##
## Residuals:
## Min 1Q Median 3Q Max
## -64.870 -14.564 5.472 20.904 36.246
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 65.19452 1.42953 45.606 <2e-16 ***
## V201507x -0.01801 0.02690 -0.669 0.503
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 27.51 on 3041 degrees of freedom
## Multiple R-squared: 0.0001473, Adjusted R-squared: -0.0001815
## F-statistic: 0.4481 on 1 and 3041 DF, p-value: 0.5033