AI Concern
CodeBook
setwd("C:/Users/mvx13/OneDrive - Texas State University/Papers/2025/00_NewPapers/Survey/PewSurvey/W152")
library(readxl)
library(ggplot2)
library(dplyr)
library(compareGroups)
library(vtree)
library(DT)
codebook= read_excel("ATP W152 Codebook_cleaned.xlsx", sheet="Codebook")
datatable(
codebook, extensions = 'Buttons', options = list(
dom = 'Bfrtip',
buttons = c('csv', 'excel')
)
)AI Concern
## F_METRO F_CREGION F_USR_SELFID F_AGECAT F_GENDER
## 1 Non-metropolitan Midwest Rural 65+ A man
## 2 Metropolitan South Suburban 65+ A man
## 3 Non-metropolitan Midwest Rural 50-64 A man
## 4 Metropolitan West Suburban 50-64 A woman
## 5 Non-metropolitan South Rural 50-64 A woman
## 6 Metropolitan Midwest Suburban 65+ A woman
## F_EDUCCAT F_HISP_ORIGIN F_RACETHNMOD
## 1 Some College No Response White non-Hispanic
## 2 Some College No Response White non-Hispanic
## 3 H.S. graduate or less No Response White non-Hispanic
## 4 College graduate+ No Response White non-Hispanic
## 5 College graduate+ No Response White non-Hispanic
## 6 College graduate+ No Response White non-Hispanic
## F_BIRTHPLACE F_MARITAL F_PARTYLN_FINAL
## 1 U.S. 50 states, District of Columbia Married No Response
## 2 U.S. 50 states, District of Columbia Married No Response
## 3 U.S. 50 states, District of Columbia Married No Response
## 4 U.S. 50 states, District of Columbia Married The Republican Party
## 5 U.S. 50 states, District of Columbia Never been married The Republican Party
## 6 U.S. 50 states, District of Columbia Married No Response
## F_INC_SDT1 F_IDEO F_INTFREQ
## 1 $80,000 to less than $90,000 Moderate About once a day
## 2 $100,000 or more Conservative Less often
## 3 Refused Conservative Several times a day
## 4 $90,000 to less than $100,000 Moderate Several times a day
## 5 $100,000 or more Moderate Almost constantly
## 6 $100,000 or more Conservative Several times a day
## CNCEXC_W152
## 1 More concerned than excited
## 2 More concerned than excited
## 3 Equally concerned and excited
## 4 More concerned than excited
## 5 More concerned than excited
## 6 More concerned than excitedCompare Groups
res1 <- compareGroups(CNCEXC_W152 ~ ., df1, ref = 1, max.ylev = 50,
max.xlev = 50, chisq.test.perm=TRUE, chisq.test.B=10000)
res2= createTable(res1, show.ratio = TRUE)
res2##
## --------Summary descriptives table by 'CNCEXC_W152'---------
##
## _____________________________________________________________________________________________________________________________________________________________________
## Don't know/Refused/Web blank Equally concerned and excited More concerned than excited More excited than concerned p.overall
## N=31 N=2091 N=2675 N=613
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## F_METRO: 0.019
## Metropolitan 26 (83.9%) 1846 (88.3%) 2288 (85.5%) 576 (94.0%)
## No Response 0 (0.00%) 2 (0.10%) 1 (0.04%) 0 (0.00%)
## Non-metropolitan 5 (16.1%) 243 (11.6%) 386 (14.4%) 37 (6.04%)
## F_CREGION: 0.028
## Midwest 6 (19.4%) 367 (17.6%) 592 (22.1%) 124 (20.2%)
## No Response 0 (0.00%) 2 (0.10%) 1 (0.04%) 0 (0.00%)
## Northeast 6 (19.4%) 357 (17.1%) 479 (17.9%) 93 (15.2%)
## South 10 (32.3%) 821 (39.3%) 1008 (37.7%) 237 (38.7%)
## West 9 (29.0%) 544 (26.0%) 595 (22.2%) 159 (25.9%)
## F_USR_SELFID: <0.001
## Refused 2 (6.45%) 27 (1.29%) 22 (0.82%) 6 (0.98%)
## Rural 6 (19.4%) 432 (20.7%) 713 (26.7%) 84 (13.7%)
## Suburban 15 (48.4%) 1111 (53.1%) 1352 (50.5%) 338 (55.1%)
## Urban 8 (25.8%) 521 (24.9%) 588 (22.0%) 185 (30.2%)
## F_AGECAT: <0.001
## 18-29 1 (3.23%) 313 (15.0%) 297 (11.1%) 152 (24.8%)
## 30-49 5 (16.1%) 754 (36.1%) 834 (31.2%) 290 (47.3%)
## 50-64 12 (38.7%) 491 (23.5%) 729 (27.3%) 110 (17.9%)
## 65+ 13 (41.9%) 521 (24.9%) 801 (29.9%) 60 (9.79%)
## Refused 0 (0.00%) 12 (0.57%) 14 (0.52%) 1 (0.16%)
## F_GENDER: <0.001
## A man 18 (58.1%) 1054 (50.4%) 1212 (45.3%) 405 (66.1%)
## A woman 13 (41.9%) 1018 (48.7%) 1434 (53.6%) 202 (33.0%)
## In some other way 0 (0.00%) 11 (0.53%) 18 (0.67%) 2 (0.33%)
## Refused 0 (0.00%) 8 (0.38%) 11 (0.41%) 4 (0.65%)
## F_EDUCCAT: <0.001
## College graduate+ 9 (29.0%) 951 (45.5%) 999 (37.3%) 350 (57.1%)
## H.S. graduate or less 13 (41.9%) 534 (25.5%) 797 (29.8%) 114 (18.6%)
## Refused 0 (0.00%) 4 (0.19%) 7 (0.26%) 2 (0.33%)
## Some College 9 (29.0%) 602 (28.8%) 872 (32.6%) 147 (24.0%)
## F_HISP_ORIGIN: 0.005
## Cuban 0 (0.00%) 23 (1.10%) 19 (0.71%) 10 (1.63%)
## Dominican 1 (3.23%) 17 (0.81%) 7 (0.26%) 4 (0.65%)
## Mexican 1 (3.23%) 161 (7.70%) 212 (7.93%) 61 (9.95%)
## No Response 29 (93.5%) 1769 (84.6%) 2293 (85.7%) 481 (78.5%)
## Other Central American 0 (0.00%) 15 (0.72%) 21 (0.79%) 6 (0.98%)
## Other country 0 (0.00%) 9 (0.43%) 12 (0.45%) 1 (0.16%)
## Other South American 0 (0.00%) 33 (1.58%) 37 (1.38%) 20 (3.26%)
## Puerto Rican 0 (0.00%) 32 (1.53%) 37 (1.38%) 10 (1.63%)
## Refused 0 (0.00%) 6 (0.29%) 7 (0.26%) 4 (0.65%)
## Salvadoran 0 (0.00%) 7 (0.33%) 7 (0.26%) 11 (1.79%)
## Spanish 0 (0.00%) 19 (0.91%) 23 (0.86%) 5 (0.82%)
## F_RACETHNMOD: <0.001
## Asian non-Hispanic 4 (12.9%) 273 (13.1%) 148 (5.53%) 126 (20.6%)
## Black non-Hispanic 6 (19.4%) 249 (11.9%) 308 (11.5%) 75 (12.2%)
## Hispanic 2 (6.45%) 322 (15.4%) 382 (14.3%) 132 (21.5%)
## Other 1 (3.23%) 67 (3.20%) 116 (4.34%) 27 (4.40%)
## Refused 1 (3.23%) 15 (0.72%) 26 (0.97%) 4 (0.65%)
## White non-Hispanic 17 (54.8%) 1165 (55.7%) 1695 (63.4%) 249 (40.6%)
## F_BIRTHPLACE: <0.001
## Another country 6 (19.4%) 400 (19.1%) 298 (11.1%) 178 (29.0%)
## Refused 0 (0.00%) 16 (0.77%) 14 (0.52%) 4 (0.65%)
## U.S. 50 states, District of Columbia 25 (80.6%) 1638 (78.3%) 2325 (86.9%) 418 (68.2%)
## U.S. other territory 0 (0.00%) 21 (1.00%) 15 (0.56%) 6 (0.98%)
## U.S. Puerto Rico 0 (0.00%) 16 (0.77%) 23 (0.86%) 7 (1.14%)
## F_MARITAL: <0.001
## Divorced 3 (9.68%) 176 (8.42%) 277 (10.4%) 38 (6.20%)
## Living with a partner 2 (6.45%) 183 (8.75%) 238 (8.90%) 75 (12.2%)
## Married 13 (41.9%) 1159 (55.4%) 1460 (54.6%) 304 (49.6%)
## Never been married 7 (22.6%) 442 (21.1%) 483 (18.1%) 178 (29.0%)
## Refused 0 (0.00%) 12 (0.57%) 13 (0.49%) 4 (0.65%)
## Separated 2 (6.45%) 38 (1.82%) 43 (1.61%) 9 (1.47%)
## Widowed 4 (12.9%) 81 (3.87%) 161 (6.02%) 5 (0.82%)
## F_PARTYLN_FINAL: <0.001
## No Response 19 (61.3%) 1134 (54.2%) 1589 (59.4%) 303 (49.4%)
## Refused 5 (16.1%) 71 (3.40%) 98 (3.66%) 23 (3.75%)
## The Democratic Party 3 (9.68%) 494 (23.6%) 491 (18.4%) 160 (26.1%)
## The Republican Party 4 (12.9%) 392 (18.7%) 497 (18.6%) 127 (20.7%)
## F_INC_SDT1: <0.001
## $100,000 or more 9 (29.0%) 770 (36.8%) 713 (26.7%) 249 (40.6%)
## $30,000 to less than $40,000 2 (6.45%) 158 (7.56%) 223 (8.34%) 53 (8.65%)
## $40,000 to less than $50,000 2 (6.45%) 152 (7.27%) 230 (8.60%) 32 (5.22%)
## $50,000 to less than $60,000 1 (3.23%) 145 (6.93%) 196 (7.33%) 36 (5.87%)
## $60,000 to less than $70,000 0 (0.00%) 135 (6.46%) 197 (7.36%) 37 (6.04%)
## $70,000 to less than $80,000 3 (9.68%) 130 (6.22%) 198 (7.40%) 39 (6.36%)
## $80,000 to less than $90,000 0 (0.00%) 105 (5.02%) 170 (6.36%) 29 (4.73%)
## $90,000 to less than $100,000 2 (6.45%) 112 (5.36%) 177 (6.62%) 36 (5.87%)
## Less than $30,000 9 (29.0%) 289 (13.8%) 432 (16.1%) 79 (12.9%)
## Refused 3 (9.68%) 95 (4.54%) 139 (5.20%) 23 (3.75%)
## F_IDEO: <0.001
## Conservative 9 (29.0%) 454 (21.7%) 733 (27.4%) 118 (19.2%)
## Liberal 4 (12.9%) 443 (21.2%) 414 (15.5%) 121 (19.7%)
## Moderate 11 (35.5%) 886 (42.4%) 939 (35.1%) 291 (47.5%)
## Refused 3 (9.68%) 26 (1.24%) 70 (2.62%) 9 (1.47%)
## Very conservative 2 (6.45%) 132 (6.31%) 299 (11.2%) 31 (5.06%)
## Very liberal 2 (6.45%) 150 (7.17%) 220 (8.22%) 43 (7.01%)
## F_INTFREQ: <0.001
## About once a day 2 (6.45%) 74 (3.54%) 134 (5.01%) 17 (2.77%)
## Almost constantly 11 (35.5%) 1063 (50.8%) 1135 (42.4%) 420 (68.5%)
## Do not use the internet 3 (9.68%) 34 (1.63%) 44 (1.64%) 3 (0.49%)
## Less often 2 (6.45%) 33 (1.58%) 53 (1.98%) 4 (0.65%)
## Refused 0 (0.00%) 9 (0.43%) 10 (0.37%) 4 (0.65%)
## Several times a day 10 (32.3%) 839 (40.1%) 1232 (46.1%) 155 (25.3%)
## Several times a week 3 (9.68%) 39 (1.87%) 67 (2.50%) 10 (1.63%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯Chi-sq Test
g <- "CNCEXC_W152"
vars <- c("F_METRO", "F_CREGION", "F_USR_SELFID", "F_AGECAT", "F_GENDER", "F_EDUCCAT", "F_HISP_ORIGIN", "F_RACETHNMOD",
"F_BIRTHPLACE", "F_MARITAL", "F_PARTYLN_FINAL", "F_INC_SDT1", "F_IDEO", "F_INTFREQ")
chisq_info <- lapply(vars, function(v){
tab <- table(df1[[v]], df1[[g]])
ct <- suppressWarnings(chisq.test(tab, correct = FALSE))
data.frame(
var = v,
chisq = unname(ct$statistic),
df = unname(ct$parameter),
p = ct$p.value
)
})
chisq_info <- do.call(rbind, chisq_info)
chisq_info## var chisq df p
## 1 F_METRO 35.69887 6 3.154103e-06
## 2 F_CREGION 24.91512 12 1.523025e-02
## 3 F_USR_SELFID 72.92651 9 4.051097e-12
## 4 F_AGECAT 218.49764 12 4.862878e-40
## 5 F_GENDER 90.22228 9 1.469158e-15
## 6 F_EDUCCAT 95.79310 9 1.112839e-16
## 7 F_HISP_ORIGIN 67.42629 30 1.064247e-04
## 8 F_RACETHNMOD 213.98910 15 3.009686e-37
## 9 F_BIRTHPLACE 146.59153 12 2.782916e-25
## 10 F_MARITAL 95.00487 18 1.803664e-12
## 11 F_PARTYLN_FINAL 51.79301 9 4.946525e-08
## 12 F_INC_SDT1 95.94595 27 1.180376e-09
## 13 F_IDEO 138.96135 15 3.688748e-22
## 14 F_INTFREQ 177.30994 18 3.268075e-28vtree
## [1] "F_METRO" "F_CREGION" "F_USR_SELFID" "F_AGECAT"
## [5] "F_GENDER" "F_EDUCCAT" "F_HISP_ORIGIN" "F_RACETHNMOD"
## [9] "F_BIRTHPLACE" "F_MARITAL" "F_PARTYLN_FINAL" "F_INC_SDT1"
## [13] "F_IDEO" "F_INTFREQ" "CNCEXC_W152"
