Compare Groups
res1 <- compareGroups(DRIVE2_d_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 'DRIVE2_d_W152'---------
##
## _________________________________________________________________________________________________________________________
## Don't know/Refused/Web blank Major problem Minor problem Not a problem p.overall
## N=75 N=1963 N=2476 N=896
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## F_METRO: 0.004
## Metropolitan 64 (85.3%) 1748 (89.0%) 2152 (86.9%) 772 (86.2%)
## No Response 1 (1.33%) 0 (0.00%) 2 (0.08%) 0 (0.00%)
## Non-metropolitan 10 (13.3%) 215 (11.0%) 322 (13.0%) 124 (13.8%)
## F_CREGION: 0.003
## Midwest 16 (21.3%) 362 (18.4%) 518 (20.9%) 193 (21.5%)
## No Response 1 (1.33%) 0 (0.00%) 2 (0.08%) 0 (0.00%)
## Northeast 16 (21.3%) 339 (17.3%) 436 (17.6%) 144 (16.1%)
## South 27 (36.0%) 760 (38.7%) 916 (37.0%) 373 (41.6%)
## West 15 (20.0%) 502 (25.6%) 604 (24.4%) 186 (20.8%)
## F_USR_SELFID: 0.001
## Refused 0 (0.00%) 22 (1.12%) 20 (0.81%) 15 (1.67%)
## Rural 23 (30.7%) 429 (21.9%) 558 (22.5%) 225 (25.1%)
## Suburban 32 (42.7%) 979 (49.9%) 1358 (54.8%) 447 (49.9%)
## Urban 20 (26.7%) 533 (27.2%) 540 (21.8%) 209 (23.3%)
## F_AGECAT: <0.001
## 18-29 9 (12.0%) 244 (12.4%) 360 (14.5%) 150 (16.7%)
## 30-49 11 (14.7%) 665 (33.9%) 797 (32.2%) 410 (45.8%)
## 50-64 13 (17.3%) 543 (27.7%) 628 (25.4%) 158 (17.6%)
## 65+ 40 (53.3%) 497 (25.3%) 684 (27.6%) 174 (19.4%)
## Refused 2 (2.67%) 14 (0.71%) 7 (0.28%) 4 (0.45%)
## F_GENDER: 0.001
## A man 21 (28.0%) 914 (46.6%) 1279 (51.7%) 475 (53.0%)
## A woman 52 (69.3%) 1035 (52.7%) 1172 (47.3%) 408 (45.5%)
## In some other way 0 (0.00%) 5 (0.25%) 17 (0.69%) 9 (1.00%)
## Refused 2 (2.67%) 9 (0.46%) 8 (0.32%) 4 (0.45%)
## F_EDUCCAT: <0.001
## College graduate+ 32 (42.7%) 733 (37.3%) 1175 (47.5%) 369 (41.2%)
## H.S. graduate or less 27 (36.0%) 607 (30.9%) 577 (23.3%) 247 (27.6%)
## Refused 2 (2.67%) 4 (0.20%) 4 (0.16%) 3 (0.33%)
## Some College 14 (18.7%) 619 (31.5%) 720 (29.1%) 277 (30.9%)
## F_HISP_ORIGIN: <0.001
## Cuban 0 (0.00%) 28 (1.43%) 22 (0.89%) 2 (0.22%)
## Dominican 1 (1.33%) 13 (0.66%) 11 (0.44%) 4 (0.45%)
## Mexican 8 (10.7%) 204 (10.4%) 169 (6.83%) 54 (6.03%)
## No Response 60 (80.0%) 1560 (79.5%) 2165 (87.4%) 787 (87.8%)
## Other Central American 1 (1.33%) 25 (1.27%) 11 (0.44%) 5 (0.56%)
## Other country 1 (1.33%) 9 (0.46%) 9 (0.36%) 3 (0.33%)
## Other South American 2 (2.67%) 45 (2.29%) 32 (1.29%) 11 (1.23%)
## Puerto Rican 0 (0.00%) 38 (1.94%) 27 (1.09%) 14 (1.56%)
## Refused 2 (2.67%) 8 (0.41%) 6 (0.24%) 1 (0.11%)
## Salvadoran 0 (0.00%) 14 (0.71%) 8 (0.32%) 3 (0.33%)
## Spanish 0 (0.00%) 19 (0.97%) 16 (0.65%) 12 (1.34%)
## F_RACETHNMOD: <0.001
## Asian non-Hispanic 6 (8.00%) 217 (11.1%) 234 (9.45%) 94 (10.5%)
## Black non-Hispanic 8 (10.7%) 285 (14.5%) 231 (9.33%) 114 (12.7%)
## Hispanic 15 (20.0%) 403 (20.5%) 311 (12.6%) 109 (12.2%)
## Other 2 (2.67%) 65 (3.31%) 98 (3.96%) 46 (5.13%)
## Refused 0 (0.00%) 16 (0.82%) 19 (0.77%) 11 (1.23%)
## White non-Hispanic 44 (58.7%) 977 (49.8%) 1583 (63.9%) 522 (58.3%)
## F_BIRTHPLACE: <0.001
## Another country 10 (13.3%) 432 (22.0%) 340 (13.7%) 100 (11.2%)
## Refused 2 (2.67%) 20 (1.02%) 9 (0.36%) 3 (0.33%)
## U.S. 50 states, District of Columbia 61 (81.3%) 1465 (74.6%) 2100 (84.8%) 780 (87.1%)
## U.S. other territory 1 (1.33%) 23 (1.17%) 13 (0.53%) 5 (0.56%)
## U.S. Puerto Rico 1 (1.33%) 23 (1.17%) 14 (0.57%) 8 (0.89%)
## F_MARITAL: <0.001
## Divorced 9 (12.0%) 201 (10.2%) 210 (8.48%) 74 (8.26%)
## Living with a partner 4 (5.33%) 173 (8.81%) 210 (8.48%) 111 (12.4%)
## Married 37 (49.3%) 1082 (55.1%) 1362 (55.0%) 455 (50.8%)
## Never been married 14 (18.7%) 370 (18.8%) 514 (20.8%) 212 (23.7%)
## Refused 4 (5.33%) 12 (0.61%) 8 (0.32%) 5 (0.56%)
## Separated 2 (2.67%) 32 (1.63%) 47 (1.90%) 11 (1.23%)
## Widowed 5 (6.67%) 93 (4.74%) 125 (5.05%) 28 (3.12%)
## F_PARTYLN_FINAL: 0.003
## No Response 39 (52.0%) 1124 (57.3%) 1427 (57.6%) 455 (50.8%)
## Refused 5 (6.67%) 79 (4.02%) 80 (3.23%) 33 (3.68%)
## The Democratic Party 19 (25.3%) 377 (19.2%) 522 (21.1%) 230 (25.7%)
## The Republican Party 12 (16.0%) 383 (19.5%) 447 (18.1%) 178 (19.9%)
## F_INC_SDT1: <0.001
## $100,000 or more 15 (20.0%) 548 (27.9%) 897 (36.2%) 281 (31.4%)
## $30,000 to less than $40,000 2 (2.67%) 193 (9.83%) 173 (6.99%) 68 (7.59%)
## $40,000 to less than $50,000 7 (9.33%) 155 (7.90%) 188 (7.59%) 66 (7.37%)
## $50,000 to less than $60,000 4 (5.33%) 144 (7.34%) 176 (7.11%) 54 (6.03%)
## $60,000 to less than $70,000 3 (4.00%) 124 (6.32%) 158 (6.38%) 84 (9.38%)
## $70,000 to less than $80,000 4 (5.33%) 123 (6.27%) 172 (6.95%) 71 (7.92%)
## $80,000 to less than $90,000 2 (2.67%) 115 (5.86%) 147 (5.94%) 40 (4.46%)
## $90,000 to less than $100,000 3 (4.00%) 121 (6.16%) 152 (6.14%) 51 (5.69%)
## Less than $30,000 21 (28.0%) 330 (16.8%) 309 (12.5%) 149 (16.6%)
## Refused 14 (18.7%) 110 (5.60%) 104 (4.20%) 32 (3.57%)
## F_IDEO: <0.001
## Conservative 10 (13.3%) 524 (26.7%) 614 (24.8%) 166 (18.5%)
## Liberal 15 (20.0%) 276 (14.1%) 495 (20.0%) 196 (21.9%)
## Moderate 27 (36.0%) 810 (41.3%) 940 (38.0%) 350 (39.1%)
## Refused 8 (10.7%) 42 (2.14%) 40 (1.62%) 18 (2.01%)
## Very conservative 12 (16.0%) 212 (10.8%) 183 (7.39%) 57 (6.36%)
## Very liberal 3 (4.00%) 99 (5.04%) 204 (8.24%) 109 (12.2%)
## F_INTFREQ: <0.001
## About once a day 5 (6.67%) 83 (4.23%) 109 (4.40%) 30 (3.35%)
## Almost constantly 24 (32.0%) 976 (49.7%) 1147 (46.3%) 482 (53.8%)
## Do not use the internet 5 (6.67%) 36 (1.83%) 30 (1.21%) 13 (1.45%)
## Less often 7 (9.33%) 45 (2.29%) 28 (1.13%) 12 (1.34%)
## Refused 2 (2.67%) 9 (0.46%) 9 (0.36%) 3 (0.33%)
## Several times a day 32 (42.7%) 769 (39.2%) 1100 (44.4%) 335 (37.4%)
## Several times a week 0 (0.00%) 45 (2.29%) 53 (2.14%) 21 (2.34%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
##export2xls(res2, file='tabledem_Driver1.xlsx')
df3= df[, c(16:21, 4)]
res1 <- compareGroups(F_AGECAT ~ ., df3, 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 'F_AGECAT'---------
##
## ________________________________________________________________________________________________________
## 18-29 30-49 50-64 65+ Refused p.overall
## N=763 N=1883 N=1342 N=1395 N=27
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## DRIVE2_a_W152: 0.003
## Don't know/Refused/Web blank 5 (0.66%) 2 (0.11%) 2 (0.15%) 7 (0.50%) 1 (3.70%)
## Major problem 456 (59.8%) 1122 (59.6%) 864 (64.4%) 911 (65.3%) 19 (70.4%)
## Minor problem 240 (31.5%) 628 (33.4%) 422 (31.4%) 405 (29.0%) 5 (18.5%)
## Not a problem 62 (8.13%) 131 (6.96%) 54 (4.02%) 72 (5.16%) 2 (7.41%)
## DRIVE2_b_W152: 0.011
## Don't know/Refused/Web blank 5 (0.66%) 3 (0.16%) 1 (0.07%) 5 (0.36%) 1 (3.70%)
## Major problem 483 (63.3%) 1162 (61.7%) 887 (66.1%) 881 (63.2%) 18 (66.7%)
## Minor problem 220 (28.8%) 606 (32.2%) 386 (28.8%) 423 (30.3%) 7 (25.9%)
## Not a problem 55 (7.21%) 112 (5.95%) 68 (5.07%) 86 (6.16%) 1 (3.70%)
## DRIVE2_c_W152: <0.001
## Don't know/Refused/Web blank 5 (0.66%) 7 (0.37%) 7 (0.52%) 18 (1.29%) 2 (7.41%)
## Major problem 387 (50.7%) 957 (50.8%) 656 (48.9%) 660 (47.3%) 17 (63.0%)
## Minor problem 289 (37.9%) 775 (41.2%) 613 (45.7%) 642 (46.0%) 3 (11.1%)
## Not a problem 82 (10.7%) 144 (7.65%) 66 (4.92%) 75 (5.38%) 5 (18.5%)
## DRIVE2_d_W152: <0.001
## Don't know/Refused/Web blank 9 (1.18%) 11 (0.58%) 13 (0.97%) 40 (2.87%) 2 (7.41%)
## Major problem 244 (32.0%) 665 (35.3%) 543 (40.5%) 497 (35.6%) 14 (51.9%)
## Minor problem 360 (47.2%) 797 (42.3%) 628 (46.8%) 684 (49.0%) 7 (25.9%)
## Not a problem 150 (19.7%) 410 (21.8%) 158 (11.8%) 174 (12.5%) 4 (14.8%)
## DRIVE2_e_W152: 0.001
## Don't know/Refused/Web blank 4 (0.52%) 3 (0.16%) 3 (0.22%) 2 (0.14%) 1 (3.70%)
## Major problem 575 (75.4%) 1491 (79.2%) 1103 (82.2%) 1062 (76.1%) 22 (81.5%)
## Minor problem 152 (19.9%) 330 (17.5%) 208 (15.5%) 303 (21.7%) 3 (11.1%)
## Not a problem 32 (4.19%) 59 (3.13%) 28 (2.09%) 28 (2.01%) 1 (3.70%)
## DRIVE2_f_W152: 0.001
## Don't know/Refused/Web blank 5 (0.66%) 2 (0.11%) 4 (0.30%) 7 (0.50%) 2 (7.41%)
## Major problem 350 (45.9%) 907 (48.2%) 637 (47.5%) 634 (45.4%) 12 (44.4%)
## Minor problem 312 (40.9%) 761 (40.4%) 573 (42.7%) 616 (44.2%) 9 (33.3%)
## Not a problem 96 (12.6%) 213 (11.3%) 128 (9.54%) 138 (9.89%) 4 (14.8%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
##export2xls(res2, file='tabledem_Driver1.xlsx')
df3= df[, c(16:21, 15)]
res1 <- compareGroups(DRIVE1_W152 ~ ., df3, 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 'DRIVE1_W152'---------
##
## ___________________________________________________________________________________________________________________________________________________________________________________
## A lot less safely A lot more safely Neither more nor less safely Not sure Refused/Web blank Somewhat less safely Somewhat more safely p.overall
## N=1245 N=93 N=1922 N=326 N=8 N=1431 N=385
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## DRIVE2_a_W152: <0.001
## Don't know/Refused/Web blank 1 (0.08%) 0 (0.00%) 5 (0.26%) 3 (0.92%) 2 (25.0%) 3 (0.21%) 3 (0.78%)
## Major problem 1061 (85.2%) 49 (52.7%) 905 (47.1%) 170 (52.1%) 3 (37.5%) 1001 (70.0%) 183 (47.5%)
## Minor problem 165 (13.3%) 36 (38.7%) 845 (44.0%) 108 (33.1%) 2 (25.0%) 395 (27.6%) 149 (38.7%)
## Not a problem 18 (1.45%) 8 (8.60%) 167 (8.69%) 45 (13.8%) 1 (12.5%) 32 (2.24%) 50 (13.0%)
## DRIVE2_b_W152: <0.001
## Don't know/Refused/Web blank 2 (0.16%) 0 (0.00%) 3 (0.16%) 4 (1.23%) 2 (25.0%) 2 (0.14%) 2 (0.52%)
## Major problem 1103 (88.6%) 49 (52.7%) 928 (48.3%) 177 (54.3%) 2 (25.0%) 999 (69.8%) 173 (44.9%)
## Minor problem 127 (10.2%) 33 (35.5%) 822 (42.8%) 105 (32.2%) 3 (37.5%) 388 (27.1%) 164 (42.6%)
## Not a problem 13 (1.04%) 11 (11.8%) 169 (8.79%) 40 (12.3%) 1 (12.5%) 42 (2.94%) 46 (11.9%)
## DRIVE2_c_W152: <0.001
## Don't know/Refused/Web blank 5 (0.40%) 0 (0.00%) 10 (0.52%) 9 (2.76%) 2 (25.0%) 9 (0.63%) 4 (1.04%)
## Major problem 796 (63.9%) 46 (49.5%) 818 (42.6%) 163 (50.0%) 2 (25.0%) 697 (48.7%) 155 (40.3%)
## Minor problem 405 (32.5%) 34 (36.6%) 926 (48.2%) 106 (32.5%) 3 (37.5%) 653 (45.6%) 195 (50.6%)
## Not a problem 39 (3.13%) 13 (14.0%) 168 (8.74%) 48 (14.7%) 1 (12.5%) 72 (5.03%) 31 (8.05%)
## DRIVE2_d_W152: <0.001
## Don't know/Refused/Web blank 11 (0.88%) 0 (0.00%) 27 (1.40%) 11 (3.37%) 2 (25.0%) 16 (1.12%) 8 (2.08%)
## Major problem 611 (49.1%) 36 (38.7%) 551 (28.7%) 123 (37.7%) 1 (12.5%) 520 (36.3%) 121 (31.4%)
## Minor problem 484 (38.9%) 37 (39.8%) 962 (50.1%) 113 (34.7%) 4 (50.0%) 701 (49.0%) 175 (45.5%)
## Not a problem 139 (11.2%) 20 (21.5%) 382 (19.9%) 79 (24.2%) 1 (12.5%) 194 (13.6%) 81 (21.0%)
## DRIVE2_e_W152: <0.001
## Don't know/Refused/Web blank 0 (0.00%) 0 (0.00%) 6 (0.31%) 1 (0.31%) 2 (25.0%) 3 (0.21%) 1 (0.26%)
## Major problem 1162 (93.3%) 60 (64.5%) 1350 (70.2%) 227 (69.6%) 3 (37.5%) 1198 (83.7%) 253 (65.7%)
## Minor problem 73 (5.86%) 27 (29.0%) 505 (26.3%) 67 (20.6%) 2 (25.0%) 210 (14.7%) 112 (29.1%)
## Not a problem 10 (0.80%) 6 (6.45%) 61 (3.17%) 31 (9.51%) 1 (12.5%) 20 (1.40%) 19 (4.94%)
## DRIVE2_f_W152: <0.001
## Don't know/Refused/Web blank 2 (0.16%) 0 (0.00%) 5 (0.26%) 4 (1.23%) 2 (25.0%) 4 (0.28%) 3 (0.78%)
## Major problem 884 (71.0%) 40 (43.0%) 637 (33.1%) 149 (45.7%) 2 (25.0%) 698 (48.8%) 130 (33.8%)
## Minor problem 323 (25.9%) 35 (37.6%) 967 (50.3%) 117 (35.9%) 4 (50.0%) 637 (44.5%) 188 (48.8%)
## Not a problem 36 (2.89%) 18 (19.4%) 313 (16.3%) 56 (17.2%) 0 (0.00%) 92 (6.43%) 64 (16.6%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
df3= df[, c(16:21, 22)]
res1 <- compareGroups(DRIVE3_W152 ~ ., df3, 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 'DRIVE3_W152'---------
##
## _______________________________________________________________________________________________________________________________________
## Don't know/Refused/Web blank Extremely often Never Rarely Sometimes Very often p.overall
## N=11 N=373 N=185 N=1334 N=2446 N=1061
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## DRIVE2_a_W152: <0.001
## Don't know/Refused/Web blank 4 (36.4%) 2 (0.54%) 1 (0.54%) 3 (0.22%) 4 (0.16%) 3 (0.28%)
## Major problem 6 (54.5%) 326 (87.4%) 67 (36.2%) 555 (41.6%) 1566 (64.0%) 852 (80.3%)
## Minor problem 0 (0.00%) 33 (8.85%) 76 (41.1%) 631 (47.3%) 776 (31.7%) 184 (17.3%)
## Not a problem 1 (9.09%) 12 (3.22%) 41 (22.2%) 145 (10.9%) 100 (4.09%) 22 (2.07%)
## DRIVE2_b_W152: <0.001
## Don't know/Refused/Web blank 5 (45.5%) 2 (0.54%) 1 (0.54%) 3 (0.22%) 3 (0.12%) 1 (0.09%)
## Major problem 4 (36.4%) 345 (92.5%) 62 (33.5%) 491 (36.8%) 1624 (66.4%) 905 (85.3%)
## Minor problem 1 (9.09%) 15 (4.02%) 63 (34.1%) 685 (51.3%) 738 (30.2%) 140 (13.2%)
## Not a problem 1 (9.09%) 11 (2.95%) 59 (31.9%) 155 (11.6%) 81 (3.31%) 15 (1.41%)
## DRIVE2_c_W152: <0.001
## Don't know/Refused/Web blank 5 (45.5%) 0 (0.00%) 0 (0.00%) 14 (1.05%) 14 (0.57%) 6 (0.57%)
## Major problem 3 (27.3%) 282 (75.6%) 65 (35.1%) 404 (30.3%) 1240 (50.7%) 683 (64.4%)
## Minor problem 1 (9.09%) 77 (20.6%) 71 (38.4%) 770 (57.7%) 1069 (43.7%) 334 (31.5%)
## Not a problem 2 (18.2%) 14 (3.75%) 49 (26.5%) 146 (10.9%) 123 (5.03%) 38 (3.58%)
## DRIVE2_d_W152: <0.001
## Don't know/Refused/Web blank 5 (45.5%) 2 (0.54%) 4 (2.16%) 24 (1.80%) 30 (1.23%) 10 (0.94%)
## Major problem 3 (27.3%) 214 (57.4%) 45 (24.3%) 287 (21.5%) 901 (36.8%) 513 (48.4%)
## Minor problem 2 (18.2%) 108 (29.0%) 65 (35.1%) 733 (54.9%) 1170 (47.8%) 398 (37.5%)
## Not a problem 1 (9.09%) 49 (13.1%) 71 (38.4%) 290 (21.7%) 345 (14.1%) 140 (13.2%)
## DRIVE2_e_W152: <0.001
## Don't know/Refused/Web blank 4 (36.4%) 1 (0.27%) 0 (0.00%) 2 (0.15%) 3 (0.12%) 3 (0.28%)
## Major problem 6 (54.5%) 341 (91.4%) 95 (51.4%) 884 (66.3%) 1977 (80.8%) 950 (89.5%)
## Minor problem 1 (9.09%) 23 (6.17%) 64 (34.6%) 402 (30.1%) 416 (17.0%) 90 (8.48%)
## Not a problem 0 (0.00%) 8 (2.14%) 26 (14.1%) 46 (3.45%) 50 (2.04%) 18 (1.70%)
## DRIVE2_f_W152: <0.001
## Don't know/Refused/Web blank 5 (45.5%) 1 (0.27%) 1 (0.54%) 3 (0.22%) 8 (0.33%) 2 (0.19%)
## Major problem 4 (36.4%) 295 (79.1%) 55 (29.7%) 359 (26.9%) 1134 (46.4%) 693 (65.3%)
## Minor problem 1 (9.09%) 61 (16.4%) 65 (35.1%) 728 (54.6%) 1103 (45.1%) 313 (29.5%)
## Not a problem 1 (9.09%) 16 (4.29%) 64 (34.6%) 244 (18.3%) 201 (8.22%) 53 (5.00%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
df3= df[, c(16:21, 23)]
res1 <- compareGroups(DRIVER_W152 ~ ., df3, 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 'DRIVER_W152'---------
##
## _______________________________________________________________________________________________________________________________________________________________
## A few times a month A few times a week Daily Don't know/Refused/Web blank Never Once a week Seldom p.overall
## N=168 N=1201 N=3384 N=23 N=276 N=161 N=197
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## DRIVE2_a_W152: <0.001
## Don't know/Refused/Web blank 1 (0.60%) 2 (0.17%) 5 (0.15%) 3 (13.0%) 3 (1.09%) 1 (0.62%) 2 (1.02%)
## Major problem 101 (60.1%) 725 (60.4%) 2156 (63.7%) 14 (60.9%) 160 (58.0%) 89 (55.3%) 127 (64.5%)
## Minor problem 45 (26.8%) 413 (34.4%) 1046 (30.9%) 5 (21.7%) 78 (28.3%) 61 (37.9%) 52 (26.4%)
## Not a problem 21 (12.5%) 61 (5.08%) 177 (5.23%) 1 (4.35%) 35 (12.7%) 10 (6.21%) 16 (8.12%)
## DRIVE2_b_W152: <0.001
## Don't know/Refused/Web blank 0 (0.00%) 3 (0.25%) 4 (0.12%) 3 (13.0%) 3 (1.09%) 1 (0.62%) 1 (0.51%)
## Major problem 91 (54.2%) 755 (62.9%) 2212 (65.4%) 13 (56.5%) 160 (58.0%) 82 (50.9%) 118 (59.9%)
## Minor problem 61 (36.3%) 381 (31.7%) 995 (29.4%) 6 (26.1%) 71 (25.7%) 67 (41.6%) 61 (31.0%)
## Not a problem 16 (9.52%) 62 (5.16%) 173 (5.11%) 1 (4.35%) 42 (15.2%) 11 (6.83%) 17 (8.63%)
## DRIVE2_c_W152: <0.001
## Don't know/Refused/Web blank 0 (0.00%) 13 (1.08%) 14 (0.41%) 3 (13.0%) 4 (1.45%) 1 (0.62%) 4 (2.03%)
## Major problem 78 (46.4%) 545 (45.4%) 1724 (50.9%) 12 (52.2%) 148 (53.6%) 69 (42.9%) 101 (51.3%)
## Minor problem 64 (38.1%) 557 (46.4%) 1451 (42.9%) 8 (34.8%) 88 (31.9%) 78 (48.4%) 76 (38.6%)
## Not a problem 26 (15.5%) 86 (7.16%) 195 (5.76%) 0 (0.00%) 36 (13.0%) 13 (8.07%) 16 (8.12%)
## DRIVE2_d_W152: <0.001
## Don't know/Refused/Web blank 1 (0.60%) 30 (2.50%) 27 (0.80%) 3 (13.0%) 7 (2.54%) 3 (1.86%) 4 (2.03%)
## Major problem 61 (36.3%) 390 (32.5%) 1293 (38.2%) 10 (43.5%) 91 (33.0%) 52 (32.3%) 66 (33.5%)
## Minor problem 70 (41.7%) 585 (48.7%) 1541 (45.5%) 7 (30.4%) 105 (38.0%) 80 (49.7%) 88 (44.7%)
## Not a problem 36 (21.4%) 196 (16.3%) 523 (15.5%) 3 (13.0%) 73 (26.4%) 26 (16.1%) 39 (19.8%)
## DRIVE2_e_W152: <0.001
## Don't know/Refused/Web blank 0 (0.00%) 2 (0.17%) 5 (0.15%) 3 (13.0%) 2 (0.72%) 0 (0.00%) 1 (0.51%)
## Major problem 108 (64.3%) 919 (76.5%) 2780 (82.2%) 16 (69.6%) 180 (65.2%) 110 (68.3%) 140 (71.1%)
## Minor problem 47 (28.0%) 250 (20.8%) 541 (16.0%) 3 (13.0%) 70 (25.4%) 43 (26.7%) 42 (21.3%)
## Not a problem 13 (7.74%) 30 (2.50%) 58 (1.71%) 1 (4.35%) 24 (8.70%) 8 (4.97%) 14 (7.11%)
## DRIVE2_f_W152: <0.001
## Don't know/Refused/Web blank 0 (0.00%) 6 (0.50%) 6 (0.18%) 3 (13.0%) 3 (1.09%) 0 (0.00%) 2 (1.02%)
## Major problem 87 (51.8%) 527 (43.9%) 1594 (47.1%) 9 (39.1%) 149 (54.0%) 72 (44.7%) 102 (51.8%)
## Minor problem 59 (35.1%) 547 (45.5%) 1432 (42.3%) 10 (43.5%) 78 (28.3%) 66 (41.0%) 79 (40.1%)
## Not a problem 22 (13.1%) 121 (10.1%) 352 (10.4%) 1 (4.35%) 46 (16.7%) 23 (14.3%) 14 (7.11%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Chi-sq Test
g <- "DRIVE2_d_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 30.40942 6 3.285353e-05
## 2 F_CREGION 40.45042 12 6.052041e-05
## 3 F_USR_SELFID 31.54610 9 2.384843e-04
## 4 F_AGECAT 131.70692 12 2.803137e-22
## 5 F_GENDER 47.07426 9 3.801620e-07
## 6 F_EDUCCAT 78.02606 9 3.982282e-13
## 7 F_HISP_ORIGIN 96.86910 30 5.758835e-09
## 8 F_RACETHNMOD 128.32107 15 4.530162e-20
## 9 F_BIRTHPLACE 107.76114 12 1.657185e-17
## 10 F_MARITAL 70.81264 18 3.291239e-08
## 11 F_PARTYLN_FINAL 24.86014 9 3.129855e-03
## 12 F_INC_SDT1 124.43681 27 1.841005e-14
## 13 F_IDEO 153.04878 15 5.976382e-25
## 14 F_INTFREQ 88.46223 18 2.723581e-11
vtree
## [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" "DRIVE2_d_W152"
vtree(df1,"F_GENDER DRIVE2_d_W152", showlegend=TRUE, shownodelabels=FALSE)
vtree(df1,"F_GENDER DRIVE2_d_W152", sameline=TRUE, prunesmaller=25)
#### TABLE FOR VTREE BELOW (Gender and Educat)
df2= df1[, c(6, 15)]
res1 <- compareGroups(F_EDUCCAT ~ ., df2, 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 'F_EDUCCAT'---------
##
## _________________________________________________________________________________________________________
## College graduate+ H.S. graduate or less Refused Some College p.overall
## N=2309 N=1458 N=13 N=1630
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## DRIVE2_d_W152: <0.001
## Don't know/Refused/Web blank 32 (1.39%) 27 (1.85%) 2 (15.4%) 14 (0.86%)
## Major problem 733 (31.7%) 607 (41.6%) 4 (30.8%) 619 (38.0%)
## Minor problem 1175 (50.9%) 577 (39.6%) 4 (30.8%) 720 (44.2%)
## Not a problem 369 (16.0%) 247 (16.9%) 3 (23.1%) 277 (17.0%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
vtree(df1,"F_EDUCCAT DRIVE2_d_W152", sameline=TRUE, prunesmaller=100)
df2= df1[, c(5, 15)]
res1 <- compareGroups(F_GENDER ~ ., df2, 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 'F_GENDER'---------
##
## ________________________________________________________________________________________________
## A man A woman In some other way Refused p.overall
## N=2689 N=2667 N=31 N=23
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## DRIVE2_d_W152: <0.001
## Don't know/Refused/Web blank 21 (0.78%) 52 (1.95%) 0 (0.00%) 2 (8.70%)
## Major problem 914 (34.0%) 1035 (38.8%) 5 (16.1%) 9 (39.1%)
## Minor problem 1279 (47.6%) 1172 (43.9%) 17 (54.8%) 8 (34.8%)
## Not a problem 475 (17.7%) 408 (15.3%) 9 (29.0%) 4 (17.4%)
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
vtree(df1,"F_GENDER DRIVE2_d_W152", sameline=TRUE, prunesmaller=100)
### Combined Both
vtree(df1,"F_GENDER F_EDUCCAT DRIVE2_d_W152", sameline=TRUE, prunesmaller=100)
################################
vtree(df1,"F_AGECAT F_EDUCCAT DRIVE2_d_W152", sameline=TRUE, prunesmaller=200)
vtree(df1,"F_GENDER DRIVE2_d_W152", pattern=TRUE)
vtree(df1,"F_USR_SELFID F_INC_SDT1 DRIVE2_d_W152", pattern=TRUE , prunesmaller=75)
