Urban-Rural News Media Attitudes in the US

Author

Jillian W. Reynolds

Published

June 22, 2025

Last updated: June 20, 2025 at 4:25 PM

1 Variables

  • Urbanicity

    • Urbanicity = urban / rural * 100

  • Urban-Rural Identity

    • Regardless of where you currently live, do you usually think of yourself as a city person, a suburb person, a small-town person, a country or rural person, or something else?

    • How important is being a [city person/suburb person/small-town person/country or rural person] to your identity?

For the next few items, we would like to know how important you think each one is to the United States maintaining a strong democracy.

CRIT

First, how important is it that news organizations are free to criticize political leaders?

ACCESS

Do you favor, oppose, or neither favor nor oppose elected officials restricting journalists’ access to information about government decision-making? Do you [favor / oppose] that a great deal, moderately, or a little?

CHECK

How concerned are you that some people in the government today might want to undermine the news media’s ability to serve as a check on governmental power?

TRUST

In general, how much trust and confidence do you have in the news media when it comes to reporting the news fully, accurately, and fairly?

  • Political

    • Party ID

    • Left-Right Ideology

  • Sociodemographic

    • Age

    • Education

    • Income

    • Race/Ethnicity

    • Sex

2 Analysis

⍺ = 0.05

CI = 95%

3 Results

The final sample for analysis is 6,871 respondents. Of these, 131 respondents had a different state of registration from the state of sample location (1.91%).

3.0.1 Sample Characteristics

Characteristic N = 6,871
age_CV
    Mean (SD) 52 (17)
    Median (Q1, Q3) 53 (37, 66)
    Min, Max 18, 80
    Unknown 245
income_CV
    Mean (SD) 12 (7)
    Median (Q1, Q3) 12 (6, 18)
    Min, Max 1, 22
    Unknown 436
Characteristic N = 6,8711
PTYID_CVfct
    Republican 2,879 (42%)
    Independent 792 (12%)
    Democrat 3,200 (47%)
education_CVfct
    Less than high school credential 282 (4.2%)
    High school credential 1,073 (16%)
    Some post-high school, no bachelor's degree 2,323 (34%)
    Bachelor's degree 1,750 (26%)
    Graduate degree 1,345 (20%)
    Unknown 98
race_CVfct
    White, non-Hispanic 5,022 (74%)
    Black, non-Hispanic 580 (8.5%)
    Hispanic 612 (9.0%)
    Asian/NHPI, non-Hispanic 230 (3.4%)
    NA/AN or other, non-Hispanic 149 (2.2%)
    Multiple races, non-Hispanic 218 (3.2%)
    Unknown 60
sex_CVfct
    Male 3,150 (46%)
    Female 3,683 (54%)
    Unknown 38
1 n (%)

3.0.2 Counts and Missing Values

variable n NA_count
urbanicity 6871 0
identity 6709 162
CRIT 6845 26
ACCESS 6843 28
CHECK 6834 37
TRUST 6863 8

Complete cases: 6218

variable n NA_count
age_CV 6626 245
education_CV 6773 98
income_CV 6435 436
race_CV 6811 60
sex_CV 6833 38

  • Cases with a missing value for urbanicity

  • Cases missing either party ID or left-right ideology

  • For correlation of urbanicity and attitudes, cases with a missing value for the particular attitude

  • For correlation of identity and attitudes, cases missing an identity value and cases with a missing value for the particular attitude

  • In correlation matrix, pairwise removals

  • In regression models, any cases with a missing value for the dependent variable and any incomplete cases across the sociodemographic controls

3.0.3 Means

Variable Means
variable mean mean_se mean_low mean_upp sd
urbanicity 78.835 0.382 78.068 79.602 19.704
identity  4.836 0.036  4.764  4.908  1.875
CRIT  3.627 0.022  3.583  3.67   1.332
ACCESS  3.619 0.021  3.576  3.662  1.282
CHECK  3.339 0.024  3.29   3.387  1.358
TRUST  2.371 0.021  2.328  2.413  1.19 
PTYID_CV  3.938 0.04   3.857  4.018  2.217
LRSELF_CV  5.715 0.052  5.61   5.82   2.714

3.1 Political Control Variables

3.1.1 Party ID

1 = Strong Democrat
2 = Not very strong Democrat
3 = Independent-Democrat
4 = Independent
5 = Independent-Republican
6 = Not very strong Republican
7 = Strong Republican

variable quantile_q25 quantile_q50 quantile_q75
PTYID_CV 2  4  6 
PTYID_CV p p_se p_low p_upp
1  0.216 0.007 0.203 0.23 
2  0.118 0.006 0.106 0.132
3  0.114 0.005 0.104 0.126
4  0.134 0.007 0.121 0.148
5  0.103 0.004 0.095 0.113
6  0.109 0.005 0.099 0.119
7  0.205 0.007 0.192 0.22 
variable mean mean_se mean_low mean_upp sd
PTYID_CV  3.938 0.04   3.857  4.018  2.217

3.1.2 Left-Right Ideology

0 = Left
10 = Right

variable quantile_q25 quantile_q50 quantile_q75
LRSELF_CV 4  5  8 
LRSELF_CV p p_se p_low p_upp
 0  0.045 0.004 0.037 0.054
 1  0.028 0.002 0.024 0.033
 2  0.058 0.004 0.051 0.067
 3  0.07  0.004 0.062 0.079
 4  0.077 0.004 0.069 0.086
 5  0.252 0.007 0.238 0.266
 6  0.081 0.004 0.073 0.09 
 7  0.101 0.005 0.092 0.111
 8  0.11  0.005 0.1   0.12 
 9  0.055 0.004 0.048 0.063
10  0.123 0.006 0.111 0.136
variable mean mean_se mean_low mean_upp sd
LRSELF_CV  5.715 0.052  5.61   5.82   2.714

3.2 News Media Attitudes

Unweighted

variable quantile_q25 quantile_q50 quantile_q75
CRIT 3  4     5 
ACCESS 3  3.667 5 
CHECK 2  3     5 
TRUST 1  2     3 

CRIT

CRIT p p_se p_low p_upp
1  0.11  0.006 0.1   0.122
2  0.079 0.004 0.072 0.088
3  0.241 0.007 0.227 0.255
4  0.208 0.007 0.193 0.223
5  0.358 0.008 0.343 0.374
NA 0.003 6.817 × 10−4 0.002 0.005

CRIT

ACCESS

ACCESS p p_se p_low p_upp
1     0.076 0.005 0.068 0.086
1.667 0.072 0.004 0.064 0.082
2.333 0.018 0.003 0.014 0.024
3     0.312 0.007 0.299 0.326
3.667 0.033 0.003 0.027 0.04 
4.333 0.17  0.007 0.157 0.183
5     0.315 0.007 0.301 0.33 
NA 0.002 5.426 × 10−4 0.002 0.004

ACCESS

CHECK

CHECK p p_se p_low p_upp
1  0.139 0.005 0.128 0.15 
2  0.121 0.005 0.11  0.132
3  0.269 0.008 0.253 0.286
4  0.197 0.007 0.182 0.211
5  0.269 0.008 0.253 0.285
NA 0.007 0.002 0.004 0.012

CHECK

TRUST

TRUST p p_se p_low p_upp
1  0.313 0.007 0.298 0.328
2  0.23 0.007 0.216 0.244
3  0.281 0.009 0.263 0.299
4  0.125 0.006 0.113 0.138
5  0.051 0.004 0.044 0.059
NA 6.906 × 10−4 2.775 × 10−4 3.081 × 10−4 0.002

TRUST

variable mean mean_se mean_low mean_upp sd
CRIT  3.627 0.022  3.583  3.67   1.332
ACCESS  3.619 0.021  3.576  3.662  1.282
CHECK  3.339 0.024  3.29   3.387  1.358
TRUST  2.371 0.021  2.328  2.413  1.19 

Survey/population weighted Pearson correlations with complete cases only

Correlation Matrix for News Media Attitudes
variable CRIT ACCESS CHECK TRUST
CRIT 1     0.403 0.42  0.307
ACCESS 0.403 1     0.392 0.284
CHECK 0.42  0.392 1     0.463
TRUST 0.307 0.284 0.463 1    

3.3 Correlation: Urbanicity and Identity

Pearson’s correlation

corr corr_se corr_low corr_upp
0.338 0.016 0.306 0.37

3.4 Urbanicity

Urbanicity is the proportion of urban residents in a congressional district.

Urbanicity ranged from 25.13% urban to 100% urban.

Histogram

Histogram

Density Plot

Density Plot

variable quantile_q25 quantile_q50 quantile_q75
urbanicity 63.773 83.621 97.908

0 = Rural (urbanicity < 50)

1 = Urban (urbanicity ≥ 50)

urban_fct p p_se p_low p_upp
0  0.104 0.006 0.093 0.116
1  0.896 0.006 0.884 0.907
variable mean mean_se mean_low mean_upp sd
urbanicity 78.835 0.382 78.068 79.602 19.704

3.4.1 T-tests

0 = Rural (urbanicity < 50)

1 = Urban (urbanicity ≥ 50)

[[1]]

    Design-based t-test

data:  CRIT ~ urban_fct
t = 5.1401, df = 50, p-value = 4.575e-06
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.2533057 0.5782489
sample estimates:
difference in mean 
         0.4157773 
[[1]]

    Design-based t-test

data:  ACCESS ~ urban_fct
t = 3.2046, df = 50, p-value = 0.002356
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.08549376 0.37262981
sample estimates:
difference in mean 
         0.2290618 
[[1]]

    Design-based t-test

data:  CHECK ~ urban_fct
t = 4.6217, df = 50, p-value = 2.706e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.1658836 0.4208965
sample estimates:
difference in mean 
         0.2933901 
[[1]]

    Design-based t-test

data:  TRUST ~ urban_fct
t = 2.9824, df = 50, p-value = 0.004412
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.06072845 0.31124432
sample estimates:
difference in mean 
         0.1859864

3.4.2 Correlation

Urbanicity and Attitudes

Survey/population weighted Pearson’s correlation

variable corr corr_se corr_low corr_upp
CRIT 0.152 0.016 0.118 0.185
ACCESS 0.105 0.017 0.071 0.139
CHECK 0.114 0.014 0.087 0.142
TRUST 0.105 0.016 0.074 0.136

3.4.3 Regression

3.4.3.1 Models

Call:
svyolr(CRIT_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                  Value
urbanicity                                                  0.009504264
PTYID_CV                                                   -0.193677569
LRSELF_CV                                                  -0.151737575
age_CV                                                      0.011491158
education_CVfctHigh school credential                      -0.270482187
education_CVfctSome post-high school, no bachelor's degree  0.109978156
education_CVfctBachelor's degree                            0.616497091
education_CVfctGraduate degree                              0.749984991
income_CV                                                   0.027650291
race_CVfctBlack, non-Hispanic                              -0.361188172
race_CVfctHispanic                                         -0.148365728
race_CVfctAsian/NHPI, non-Hispanic                         -0.192811098
race_CVfctNA/AN or other, non-Hispanic                     -0.141774832
race_CVfctMultiple races, non-Hispanic                     -0.157060284
sex_CVfctFemale                                            -0.505878503
                                                            Std. Error
urbanicity                                                 0.001778086
PTYID_CV                                                   0.017758056
LRSELF_CV                                                  0.016853223
age_CV                                                     0.001875303
education_CVfctHigh school credential                      0.138333623
education_CVfctSome post-high school, no bachelor's degree 0.152480135
education_CVfctBachelor's degree                           0.155659117
education_CVfctGraduate degree                             0.161632563
income_CV                                                  0.004988203
race_CVfctBlack, non-Hispanic                              0.132081933
race_CVfctHispanic                                         0.091640988
race_CVfctAsian/NHPI, non-Hispanic                         0.201823143
race_CVfctNA/AN or other, non-Hispanic                     0.195942782
race_CVfctMultiple races, non-Hispanic                     0.154420444
sex_CVfctFemale                                            0.068268915
                                                               t value
urbanicity                                                   5.3452220
PTYID_CV                                                   -10.9064621
LRSELF_CV                                                   -9.0034753
age_CV                                                       6.1276273
education_CVfctHigh school credential                       -1.9552888
education_CVfctSome post-high school, no bachelor's degree   0.7212622
education_CVfctBachelor's degree                             3.9605588
education_CVfctGraduate degree                               4.6400612
income_CV                                                    5.5431366
race_CVfctBlack, non-Hispanic                               -2.7345767
race_CVfctHispanic                                          -1.6189887
race_CVfctAsian/NHPI, non-Hispanic                          -0.9553468
race_CVfctNA/AN or other, non-Hispanic                      -0.7235522
race_CVfctMultiple races, non-Hispanic                      -1.0170951
sex_CVfctFemale                                             -7.4100855

Intercepts:
    Value    Std. Error t value 
1|2  -2.5209   0.2366   -10.6543
2|3  -1.8374   0.2307    -7.9636
3|4  -0.4695   0.2294    -2.0467
4|5   0.5691   0.2214     2.5701
(666 observations deleted due to missingness)
Call:
svyolr(ACCESS_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                  Value
urbanicity                                                  0.004162427
PTYID_CV                                                   -0.231817602
LRSELF_CV                                                  -0.161130453
age_CV                                                      0.007415212
education_CVfctHigh school credential                       0.136822084
education_CVfctSome post-high school, no bachelor's degree  0.485796505
education_CVfctBachelor's degree                            0.725459615
education_CVfctGraduate degree                              0.907584979
income_CV                                                   0.009373057
race_CVfctBlack, non-Hispanic                              -0.588988824
race_CVfctHispanic                                         -0.105825206
race_CVfctAsian/NHPI, non-Hispanic                         -0.375278066
race_CVfctNA/AN or other, non-Hispanic                     -0.267229996
race_CVfctMultiple races, non-Hispanic                     -0.224259362
sex_CVfctFemale                                            -0.360569199
                                                            Std. Error
urbanicity                                                 0.001844698
PTYID_CV                                                   0.018396852
LRSELF_CV                                                  0.015431660
age_CV                                                     0.002528997
education_CVfctHigh school credential                      0.156055793
education_CVfctSome post-high school, no bachelor's degree 0.175674804
education_CVfctBachelor's degree                           0.174875869
education_CVfctGraduate degree                             0.193630830
income_CV                                                  0.005695016
race_CVfctBlack, non-Hispanic                              0.137153460
race_CVfctHispanic                                         0.105161775
race_CVfctAsian/NHPI, non-Hispanic                         0.179252398
race_CVfctNA/AN or other, non-Hispanic                     0.341089378
race_CVfctMultiple races, non-Hispanic                     0.187660706
sex_CVfctFemale                                            0.059899134
                                                               t value
urbanicity                                                   2.2564271
PTYID_CV                                                   -12.6009388
LRSELF_CV                                                  -10.4415504
age_CV                                                       2.9320766
education_CVfctHigh school credential                        0.8767511
education_CVfctSome post-high school, no bachelor's degree   2.7653169
education_CVfctBachelor's degree                             4.1484261
education_CVfctGraduate degree                               4.6871925
income_CV                                                    1.6458352
race_CVfctBlack, non-Hispanic                               -4.2943782
race_CVfctHispanic                                          -1.0063087
race_CVfctAsian/NHPI, non-Hispanic                          -2.0935735
race_CVfctNA/AN or other, non-Hispanic                      -0.7834603
race_CVfctMultiple races, non-Hispanic                      -1.1950257
sex_CVfctFemale                                             -6.0196062

Intercepts:
                                  Value    Std. Error t value 
1|1.66666666666667                 -3.6826   0.2712   -13.5809
1.66666666666667|2.33333333333333  -2.8660   0.2660   -10.7749
2.33333333333333|3                 -2.7207   0.2676   -10.1687
3|3.66666666666667                 -0.9715   0.2683    -3.6208
3.66666666666667|4.33333333333333  -0.8131   0.2647    -3.0713
4.33333333333333|5                  0.0606   0.2695     0.2249
(671 observations deleted due to missingness)
Call:
svyolr(CHECK_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                  Value
urbanicity                                                  0.004996173
PTYID_CV                                                   -0.301922672
LRSELF_CV                                                  -0.142946419
age_CV                                                      0.012793350
education_CVfctHigh school credential                       0.004120050
education_CVfctSome post-high school, no bachelor's degree  0.273032628
education_CVfctBachelor's degree                            0.260356976
education_CVfctGraduate degree                              0.385942593
income_CV                                                   0.010222748
race_CVfctBlack, non-Hispanic                              -0.380360377
race_CVfctHispanic                                         -0.026448341
race_CVfctAsian/NHPI, non-Hispanic                         -0.230629013
race_CVfctNA/AN or other, non-Hispanic                     -0.090100607
race_CVfctMultiple races, non-Hispanic                     -0.054499316
sex_CVfctFemale                                            -0.098064685
                                                            Std. Error
urbanicity                                                 0.001608272
PTYID_CV                                                   0.018736573
LRSELF_CV                                                  0.016089034
age_CV                                                     0.002111202
education_CVfctHigh school credential                      0.175209773
education_CVfctSome post-high school, no bachelor's degree 0.142288084
education_CVfctBachelor's degree                           0.159899861
education_CVfctGraduate degree                             0.176222700
income_CV                                                  0.005815120
race_CVfctBlack, non-Hispanic                              0.142175078
race_CVfctHispanic                                         0.110874167
race_CVfctAsian/NHPI, non-Hispanic                         0.175176805
race_CVfctNA/AN or other, non-Hispanic                     0.324324961
race_CVfctMultiple races, non-Hispanic                     0.257807950
sex_CVfctFemale                                            0.075452130
                                                                t value
urbanicity                                                   3.10654751
PTYID_CV                                                   -16.11408175
LRSELF_CV                                                   -8.88471127
age_CV                                                       6.05974732
education_CVfctHigh school credential                        0.02351495
education_CVfctSome post-high school, no bachelor's degree   1.91887205
education_CVfctBachelor's degree                             1.62825017
education_CVfctGraduate degree                               2.19008443
income_CV                                                    1.75796000
race_CVfctBlack, non-Hispanic                               -2.67529571
race_CVfctHispanic                                          -0.23854376
race_CVfctAsian/NHPI, non-Hispanic                          -1.31654994
race_CVfctNA/AN or other, non-Hispanic                      -0.27780966
race_CVfctMultiple races, non-Hispanic                      -0.21139502
sex_CVfctFemale                                             -1.29969407

Intercepts:
    Value    Std. Error t value 
1|2  -2.9403   0.2165   -13.5811
2|3  -2.0587   0.2164    -9.5128
3|4  -0.6530   0.2072    -3.1511
4|5   0.3956   0.2089     1.8937
(668 observations deleted due to missingness)
Call:
svyolr(TRUST_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                   Value
urbanicity                                                  0.0009260861
PTYID_CV                                                   -0.4488491845
LRSELF_CV                                                  -0.0937682278
age_CV                                                      0.0178949276
education_CVfctHigh school credential                      -0.2707220168
education_CVfctSome post-high school, no bachelor's degree -0.2536450724
education_CVfctBachelor's degree                           -0.1788075679
education_CVfctGraduate degree                             -0.1199085199
income_CV                                                   0.0004507836
race_CVfctBlack, non-Hispanic                               0.2678100605
race_CVfctHispanic                                          0.2534404981
race_CVfctAsian/NHPI, non-Hispanic                          0.4288091984
race_CVfctNA/AN or other, non-Hispanic                      0.2731577404
race_CVfctMultiple races, non-Hispanic                      0.1618565257
sex_CVfctFemale                                            -0.0620611962
                                                            Std. Error
urbanicity                                                 0.001622290
PTYID_CV                                                   0.021352547
LRSELF_CV                                                  0.021229670
age_CV                                                     0.002452448
education_CVfctHigh school credential                      0.209944616
education_CVfctSome post-high school, no bachelor's degree 0.212799277
education_CVfctBachelor's degree                           0.212713775
education_CVfctGraduate degree                             0.244959652
income_CV                                                  0.005029088
race_CVfctBlack, non-Hispanic                              0.154845467
race_CVfctHispanic                                         0.124301964
race_CVfctAsian/NHPI, non-Hispanic                         0.158122728
race_CVfctNA/AN or other, non-Hispanic                     0.241606943
race_CVfctMultiple races, non-Hispanic                     0.230782676
sex_CVfctFemale                                            0.057993399
                                                                t value
urbanicity                                                   0.57085117
PTYID_CV                                                   -21.02087284
LRSELF_CV                                                   -4.41684816
age_CV                                                       7.29676227
education_CVfctHigh school credential                       -1.28949254
education_CVfctSome post-high school, no bachelor's degree  -1.19194518
education_CVfctBachelor's degree                            -0.84060173
education_CVfctGraduate degree                              -0.48950315
income_CV                                                    0.08963527
race_CVfctBlack, non-Hispanic                                1.72953117
race_CVfctHispanic                                           2.03890984
race_CVfctAsian/NHPI, non-Hispanic                           2.71187579
race_CVfctNA/AN or other, non-Hispanic                       1.13058730
race_CVfctMultiple races, non-Hispanic                       0.70133742
sex_CVfctFemale                                             -1.07014242

Intercepts:
    Value    Std. Error t value 
1|2  -2.5807   0.2975    -8.6748
2|3  -1.3068   0.3122    -4.1862
3|4   0.4677   0.3157     1.4815
4|5   1.9789   0.3225     6.1356
(657 observations deleted due to missingness)
olr_CRIT_IV1 olr_ACCESS_IV1 olr_CHECK_IV1 olr_TRUST_IV1
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
urbanicity 0.010*** 0.004* 0.005** 0.001
(0.002) (0.002) (0.002) (0.002)
PTYID_CV -0.194*** -0.232*** -0.302*** -0.449***
(0.018) (0.018) (0.019) (0.021)
LRSELF_CV -0.152*** -0.161*** -0.143*** -0.094***
(0.017) (0.015) (0.016) (0.021)
age_CV 0.011*** 0.007** 0.013*** 0.018***
(0.002) (0.003) (0.002) (0.002)
High school credential -0.270+ 0.137 0.004 -0.271
(0.138) (0.156) (0.175) (0.210)
Some post-high school, no bachelor's degree 0.110 0.486** 0.273+ -0.254
(0.152) (0.176) (0.142) (0.213)
Bachelor's degree 0.616*** 0.725*** 0.260 -0.179
(0.156) (0.175) (0.160) (0.213)
Graduate degree 0.750*** 0.908*** 0.386* -0.120
(0.162) (0.194) (0.176) (0.245)
income_CV 0.028*** 0.009 0.010+ 0.000
(0.005) (0.006) (0.006) (0.005)
Black, non-Hispanic -0.361** -0.589*** -0.380* 0.268+
(0.132) (0.137) (0.142) (0.155)
Hispanic -0.148 -0.106 -0.026 0.253*
(0.092) (0.105) (0.111) (0.124)
Asian/NHPI, non-Hispanic -0.193 -0.375* -0.231 0.429*
(0.202) (0.179) (0.175) (0.158)
NA/AN or other, non-Hispanic -0.142 -0.267 -0.090 0.273
(0.196) (0.341) (0.324) (0.242)
Multiple races, non-Hispanic -0.157 -0.224 -0.054 0.162
(0.154) (0.188) (0.258) (0.231)
Female -0.506*** -0.361*** -0.098 -0.062
(0.068) (0.060) (0.075) (0.058)
1|2 -2.521*** -2.940*** -2.581***
(0.237) (0.217) (0.297)
2|3 -1.837*** -2.059*** -1.307***
(0.231) (0.216) (0.312)
3|4 -0.470* -0.653** 0.468
(0.229) (0.207) (0.316)
4|5 0.569* 0.396+ 1.979***
(0.221) (0.209) (0.323)
1|1.66666666666667 -3.683***
(0.271)
1.66666666666667|2.33333333333333 -2.866***
(0.266)
2.33333333333333|3 -2.721***
(0.268)
3|3.66666666666667 -0.972***
(0.268)
3.66666666666667|4.33333333333333 -0.813**
(0.265)
4.33333333333333|5 0.061
(0.269)
Num.Obs. 6205 6200 6203 6214
RMSE 3.78 3.81 3.55 2.58

3.4.3.2 Odds Ratios

Tables

Characteristic OR 95% CI
urbanicity 1.01 1.01, 1.01
PTYID_CV 0.82 0.80, 0.85
LRSELF_CV 0.86 0.83, 0.89
age_CV 1.01 1.01, 1.02
education_CVfct

    Less than high school credential — —
    High school credential 0.76 0.58, 1.00
    Some post-high school, no bachelor's degree 1.12 0.83, 1.51
    Bachelor's degree 1.85 1.37, 2.51
    Graduate degree 2.12 1.54, 2.91
income_CV 1.03 1.02, 1.04
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 0.70 0.54, 0.90
    Hispanic 0.86 0.72, 1.03
    Asian/NHPI, non-Hispanic 0.82 0.56, 1.22
    NA/AN or other, non-Hispanic 0.87 0.59, 1.27
    Multiple races, non-Hispanic 0.85 0.63, 1.16
sex_CVfct

    Male — —
    Female 0.60 0.53, 0.69
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
Characteristic OR 95% CI
urbanicity 1.00 1.00, 1.01
PTYID_CV 0.79 0.77, 0.82
LRSELF_CV 0.85 0.83, 0.88
age_CV 1.01 1.00, 1.01
education_CVfct

    Less than high school credential — —
    High school credential 1.15 0.84, 1.56
    Some post-high school, no bachelor's degree 1.63 1.15, 2.29
    Bachelor's degree 2.07 1.47, 2.91
    Graduate degree 2.48 1.70, 3.62
income_CV 1.01 1.00, 1.02
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 0.55 0.42, 0.73
    Hispanic 0.90 0.73, 1.11
    Asian/NHPI, non-Hispanic 0.69 0.48, 0.98
    NA/AN or other, non-Hispanic 0.77 0.39, 1.49
    Multiple races, non-Hispanic 0.80 0.55, 1.15
sex_CVfct

    Male — —
    Female 0.70 0.62, 0.78
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
Characteristic OR 95% CI
urbanicity 1.01 1.00, 1.01
PTYID_CV 0.74 0.71, 0.77
LRSELF_CV 0.87 0.84, 0.89
age_CV 1.01 1.01, 1.02
education_CVfct

    Less than high school credential — —
    High school credential 1.00 0.71, 1.42
    Some post-high school, no bachelor's degree 1.31 0.99, 1.74
    Bachelor's degree 1.30 0.95, 1.77
    Graduate degree 1.47 1.04, 2.08
income_CV 1.01 1.00, 1.02
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 0.68 0.52, 0.90
    Hispanic 0.97 0.78, 1.21
    Asian/NHPI, non-Hispanic 0.79 0.56, 1.12
    NA/AN or other, non-Hispanic 0.91 0.48, 1.73
    Multiple races, non-Hispanic 0.95 0.57, 1.57
sex_CVfct

    Male — —
    Female 0.91 0.78, 1.05
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
Characteristic OR 95% CI
urbanicity 1.00 1.00, 1.00
PTYID_CV 0.64 0.61, 0.67
LRSELF_CV 0.91 0.87, 0.95
age_CV 1.02 1.01, 1.02
education_CVfct

    Less than high school credential — —
    High school credential 0.76 0.51, 1.15
    Some post-high school, no bachelor's degree 0.78 0.51, 1.18
    Bachelor's degree 0.84 0.55, 1.27
    Graduate degree 0.89 0.55, 1.43
income_CV 1.00 0.99, 1.01
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 1.31 0.96, 1.77
    Hispanic 1.29 1.01, 1.64
    Asian/NHPI, non-Hispanic 1.54 1.13, 2.09
    NA/AN or other, non-Hispanic 1.31 0.82, 2.11
    Multiple races, non-Hispanic 1.18 0.75, 1.85
sex_CVfct

    Male — —
    Female 0.94 0.84, 1.05
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
term olr_CRIT_IV1 olr_ACCESS_IV1 olr_CHECK_IV1 olr_TRUST_IV1
urbanicity 1.01  1.004 1.005 1.001
PTYID_CV 0.824 0.793 0.739 0.638
LRSELF_CV 0.859 0.851 0.867 0.91 
age_CV 1.012 1.007 1.013 1.018
High school credential 0.763 1.147 1.004 0.763
Some post-high school, no bachelor's degree 1.116 1.625 1.314 0.776
Bachelor's degree 1.852 2.066 1.297 0.836
Graduate degree 2.117 2.478 1.471 0.887
income_CV 1.028 1.009 1.01  1    
Black, non-Hispanic 0.697 0.555 0.684 1.307
Hispanic 0.862 0.9   0.974 1.288
Asian/NHPI, non-Hispanic 0.825 0.687 0.794 1.535
NA/AN or other, non-Hispanic 0.868 0.765 0.914 1.314
Multiple races, non-Hispanic 0.855 0.799 0.947 1.176
Female 0.603 0.697 0.907 0.94 
1|2 0.08  NA 0.053 0.076
2|3 0.159 NA 0.128 0.271
3|4 0.625 NA 0.52  1.596
4|5 1.767 NA 1.485 7.234
1|1.66666666666667 NA 0.025 NA NA
1.66666666666667|2.33333333333333 NA 0.057 NA NA
2.33333333333333|3 NA 0.066 NA NA
3|3.66666666666667 NA 0.379 NA NA
3.66666666666667|4.33333333333333 NA 0.443 NA NA
4.33333333333333|5 NA 1.062 NA NA

3.4.3.3 Plots

3.5 Urban-Rural Identity

Rural = Small-town person or Country (or rural) person

Urban = City person or suburb person

1 = Rural identity extremely important

2 = Rural identity very important

3 = Rural identity moderately important

4 = Rural identity a little important

5.4 = Rural identity not at all important

5.6 = Urban identity not at all important

7 = Urban identity a little important

8 = Urban identity moderately important

9 = Urban identity very important

10 = Urban identity extremely important

3.5.1 Descriptive Statistics

3.5.1.1 Distributions

variable quantile_q25 quantile_q50 quantile_q75
identity 3  5  6 

3.5.1.2 Proportions

PLACEID p p_se p_low p_upp
1 0.292 0.008 0.277 0.308
2 0.258 0.008 0.242 0.274
3 0.241 0.006 0.228 0.254
4 0.191 0.006 0.178 0.204
5 0.018 0.002 0.014 0.022
NA 0.001 4.984 × 10−4 4.598 × 10−4 0.003
PLACEID_fct p p_se p_low p_upp
rural 0.431 0.009 0.414 0.448
urban 0.55  0.008 0.533 0.567
NA 0.019 0.002 0.015 0.023
identity p p_se p_low p_upp
1  0.047 0.003 0.041 0.054
2  0.085 0.004 0.077 0.095
3  0.117 0.006 0.106 0.129
4  0.071 0.004 0.063 0.08 
5  0.367 0.007 0.353 0.381
6  0.098 0.006 0.088 0.11 
7  0.126 0.006 0.114 0.14 
8  0.042 0.003 0.036 0.049
9  0.027 0.003 0.021 0.035
NA 0.019 0.002 0.016 0.024

3.5.1.3 Mean

variable mean mean_se mean_low mean_upp sd
identity  4.836 0.036  4.764  4.908  1.875

3.5.2 T-tests

[[1]]

    Design-based t-test

data:  CRIT ~ PLACEID_fct
t = 8.9556, df = 50, p-value = 5.744e-12
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.3724968 0.5878933
sample estimates:
difference in mean 
          0.480195 
[[1]]

    Design-based t-test

data:  ACCESS ~ PLACEID_fct
t = 9.3225, df = 50, p-value = 1.613e-12
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.3150907 0.4881515
sample estimates:
difference in mean 
         0.4016211 
[[1]]

    Design-based t-test

data:  CHECK ~ PLACEID_fct
t = 8.4544, df = 50, p-value = 3.324e-11
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.2822506 0.4581525
sample estimates:
difference in mean 
         0.3702015 
[[1]]

    Design-based t-test

data:  TRUST ~ PLACEID_fct
t = 9.7908, df = 50, p-value = 3.258e-13
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.2978860 0.4516511
sample estimates:
difference in mean 
         0.3747685

3.5.3 Correlation

Urban-Rural Identity and Attitudes

Survey/population weighted Pearson’s correlation

variable corr corr_se corr_low corr_upp
CRIT 0.164 0.02  0.124 0.205
ACCESS 0.146 0.018 0.111 0.182
CHECK 0.118 0.018 0.082 0.155
TRUST 0.179 0.018 0.143 0.215

3.5.4 Regression

3.5.4.1 Models

Call:
svyolr(CRIT_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                  Value
urbanicity                                                  0.009504264
PTYID_CV                                                   -0.193677569
LRSELF_CV                                                  -0.151737575
age_CV                                                      0.011491158
education_CVfctHigh school credential                      -0.270482187
education_CVfctSome post-high school, no bachelor's degree  0.109978156
education_CVfctBachelor's degree                            0.616497091
education_CVfctGraduate degree                              0.749984991
income_CV                                                   0.027650291
race_CVfctBlack, non-Hispanic                              -0.361188172
race_CVfctHispanic                                         -0.148365728
race_CVfctAsian/NHPI, non-Hispanic                         -0.192811098
race_CVfctNA/AN or other, non-Hispanic                     -0.141774832
race_CVfctMultiple races, non-Hispanic                     -0.157060284
sex_CVfctFemale                                            -0.505878503
                                                            Std. Error
urbanicity                                                 0.001778086
PTYID_CV                                                   0.017758056
LRSELF_CV                                                  0.016853223
age_CV                                                     0.001875303
education_CVfctHigh school credential                      0.138333623
education_CVfctSome post-high school, no bachelor's degree 0.152480135
education_CVfctBachelor's degree                           0.155659117
education_CVfctGraduate degree                             0.161632563
income_CV                                                  0.004988203
race_CVfctBlack, non-Hispanic                              0.132081933
race_CVfctHispanic                                         0.091640988
race_CVfctAsian/NHPI, non-Hispanic                         0.201823143
race_CVfctNA/AN or other, non-Hispanic                     0.195942782
race_CVfctMultiple races, non-Hispanic                     0.154420444
sex_CVfctFemale                                            0.068268915
                                                               t value
urbanicity                                                   5.3452220
PTYID_CV                                                   -10.9064621
LRSELF_CV                                                   -9.0034753
age_CV                                                       6.1276273
education_CVfctHigh school credential                       -1.9552888
education_CVfctSome post-high school, no bachelor's degree   0.7212622
education_CVfctBachelor's degree                             3.9605588
education_CVfctGraduate degree                               4.6400612
income_CV                                                    5.5431366
race_CVfctBlack, non-Hispanic                               -2.7345767
race_CVfctHispanic                                          -1.6189887
race_CVfctAsian/NHPI, non-Hispanic                          -0.9553468
race_CVfctNA/AN or other, non-Hispanic                      -0.7235522
race_CVfctMultiple races, non-Hispanic                      -1.0170951
sex_CVfctFemale                                             -7.4100855

Intercepts:
    Value    Std. Error t value 
1|2  -2.5209   0.2366   -10.6543
2|3  -1.8374   0.2307    -7.9636
3|4  -0.4695   0.2294    -2.0467
4|5   0.5691   0.2214     2.5701
(666 observations deleted due to missingness)
Call:
svyolr(ACCESS_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                  Value
urbanicity                                                  0.004162427
PTYID_CV                                                   -0.231817602
LRSELF_CV                                                  -0.161130453
age_CV                                                      0.007415212
education_CVfctHigh school credential                       0.136822084
education_CVfctSome post-high school, no bachelor's degree  0.485796505
education_CVfctBachelor's degree                            0.725459615
education_CVfctGraduate degree                              0.907584979
income_CV                                                   0.009373057
race_CVfctBlack, non-Hispanic                              -0.588988824
race_CVfctHispanic                                         -0.105825206
race_CVfctAsian/NHPI, non-Hispanic                         -0.375278066
race_CVfctNA/AN or other, non-Hispanic                     -0.267229996
race_CVfctMultiple races, non-Hispanic                     -0.224259362
sex_CVfctFemale                                            -0.360569199
                                                            Std. Error
urbanicity                                                 0.001844698
PTYID_CV                                                   0.018396852
LRSELF_CV                                                  0.015431660
age_CV                                                     0.002528997
education_CVfctHigh school credential                      0.156055793
education_CVfctSome post-high school, no bachelor's degree 0.175674804
education_CVfctBachelor's degree                           0.174875869
education_CVfctGraduate degree                             0.193630830
income_CV                                                  0.005695016
race_CVfctBlack, non-Hispanic                              0.137153460
race_CVfctHispanic                                         0.105161775
race_CVfctAsian/NHPI, non-Hispanic                         0.179252398
race_CVfctNA/AN or other, non-Hispanic                     0.341089378
race_CVfctMultiple races, non-Hispanic                     0.187660706
sex_CVfctFemale                                            0.059899134
                                                               t value
urbanicity                                                   2.2564271
PTYID_CV                                                   -12.6009388
LRSELF_CV                                                  -10.4415504
age_CV                                                       2.9320766
education_CVfctHigh school credential                        0.8767511
education_CVfctSome post-high school, no bachelor's degree   2.7653169
education_CVfctBachelor's degree                             4.1484261
education_CVfctGraduate degree                               4.6871925
income_CV                                                    1.6458352
race_CVfctBlack, non-Hispanic                               -4.2943782
race_CVfctHispanic                                          -1.0063087
race_CVfctAsian/NHPI, non-Hispanic                          -2.0935735
race_CVfctNA/AN or other, non-Hispanic                      -0.7834603
race_CVfctMultiple races, non-Hispanic                      -1.1950257
sex_CVfctFemale                                             -6.0196062

Intercepts:
                                  Value    Std. Error t value 
1|1.66666666666667                 -3.6826   0.2712   -13.5809
1.66666666666667|2.33333333333333  -2.8660   0.2660   -10.7749
2.33333333333333|3                 -2.7207   0.2676   -10.1687
3|3.66666666666667                 -0.9715   0.2683    -3.6208
3.66666666666667|4.33333333333333  -0.8131   0.2647    -3.0713
4.33333333333333|5                  0.0606   0.2695     0.2249
(671 observations deleted due to missingness)
Call:
svyolr(CHECK_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                  Value
urbanicity                                                  0.004996173
PTYID_CV                                                   -0.301922672
LRSELF_CV                                                  -0.142946419
age_CV                                                      0.012793350
education_CVfctHigh school credential                       0.004120050
education_CVfctSome post-high school, no bachelor's degree  0.273032628
education_CVfctBachelor's degree                            0.260356976
education_CVfctGraduate degree                              0.385942593
income_CV                                                   0.010222748
race_CVfctBlack, non-Hispanic                              -0.380360377
race_CVfctHispanic                                         -0.026448341
race_CVfctAsian/NHPI, non-Hispanic                         -0.230629013
race_CVfctNA/AN or other, non-Hispanic                     -0.090100607
race_CVfctMultiple races, non-Hispanic                     -0.054499316
sex_CVfctFemale                                            -0.098064685
                                                            Std. Error
urbanicity                                                 0.001608272
PTYID_CV                                                   0.018736573
LRSELF_CV                                                  0.016089034
age_CV                                                     0.002111202
education_CVfctHigh school credential                      0.175209773
education_CVfctSome post-high school, no bachelor's degree 0.142288084
education_CVfctBachelor's degree                           0.159899861
education_CVfctGraduate degree                             0.176222700
income_CV                                                  0.005815120
race_CVfctBlack, non-Hispanic                              0.142175078
race_CVfctHispanic                                         0.110874167
race_CVfctAsian/NHPI, non-Hispanic                         0.175176805
race_CVfctNA/AN or other, non-Hispanic                     0.324324961
race_CVfctMultiple races, non-Hispanic                     0.257807950
sex_CVfctFemale                                            0.075452130
                                                                t value
urbanicity                                                   3.10654751
PTYID_CV                                                   -16.11408175
LRSELF_CV                                                   -8.88471127
age_CV                                                       6.05974732
education_CVfctHigh school credential                        0.02351495
education_CVfctSome post-high school, no bachelor's degree   1.91887205
education_CVfctBachelor's degree                             1.62825017
education_CVfctGraduate degree                               2.19008443
income_CV                                                    1.75796000
race_CVfctBlack, non-Hispanic                               -2.67529571
race_CVfctHispanic                                          -0.23854376
race_CVfctAsian/NHPI, non-Hispanic                          -1.31654994
race_CVfctNA/AN or other, non-Hispanic                      -0.27780966
race_CVfctMultiple races, non-Hispanic                      -0.21139502
sex_CVfctFemale                                             -1.29969407

Intercepts:
    Value    Std. Error t value 
1|2  -2.9403   0.2165   -13.5811
2|3  -2.0587   0.2164    -9.5128
3|4  -0.6530   0.2072    -3.1511
4|5   0.3956   0.2089     1.8937
(668 observations deleted due to missingness)
Call:
svyolr(TRUST_DVfct ~ urbanicity + PTYID_CV + LRSELF_CV + age_CV + 
    education_CVfct + income_CV + race_CVfct + sex_CVfct, design = anes_des, 
    method = "logistic")

Coefficients:
                                                                   Value
urbanicity                                                  0.0009260861
PTYID_CV                                                   -0.4488491845
LRSELF_CV                                                  -0.0937682278
age_CV                                                      0.0178949276
education_CVfctHigh school credential                      -0.2707220168
education_CVfctSome post-high school, no bachelor's degree -0.2536450724
education_CVfctBachelor's degree                           -0.1788075679
education_CVfctGraduate degree                             -0.1199085199
income_CV                                                   0.0004507836
race_CVfctBlack, non-Hispanic                               0.2678100605
race_CVfctHispanic                                          0.2534404981
race_CVfctAsian/NHPI, non-Hispanic                          0.4288091984
race_CVfctNA/AN or other, non-Hispanic                      0.2731577404
race_CVfctMultiple races, non-Hispanic                      0.1618565257
sex_CVfctFemale                                            -0.0620611962
                                                            Std. Error
urbanicity                                                 0.001622290
PTYID_CV                                                   0.021352547
LRSELF_CV                                                  0.021229670
age_CV                                                     0.002452448
education_CVfctHigh school credential                      0.209944616
education_CVfctSome post-high school, no bachelor's degree 0.212799277
education_CVfctBachelor's degree                           0.212713775
education_CVfctGraduate degree                             0.244959652
income_CV                                                  0.005029088
race_CVfctBlack, non-Hispanic                              0.154845467
race_CVfctHispanic                                         0.124301964
race_CVfctAsian/NHPI, non-Hispanic                         0.158122728
race_CVfctNA/AN or other, non-Hispanic                     0.241606943
race_CVfctMultiple races, non-Hispanic                     0.230782676
sex_CVfctFemale                                            0.057993399
                                                                t value
urbanicity                                                   0.57085117
PTYID_CV                                                   -21.02087284
LRSELF_CV                                                   -4.41684816
age_CV                                                       7.29676227
education_CVfctHigh school credential                       -1.28949254
education_CVfctSome post-high school, no bachelor's degree  -1.19194518
education_CVfctBachelor's degree                            -0.84060173
education_CVfctGraduate degree                              -0.48950315
income_CV                                                    0.08963527
race_CVfctBlack, non-Hispanic                                1.72953117
race_CVfctHispanic                                           2.03890984
race_CVfctAsian/NHPI, non-Hispanic                           2.71187579
race_CVfctNA/AN or other, non-Hispanic                       1.13058730
race_CVfctMultiple races, non-Hispanic                       0.70133742
sex_CVfctFemale                                             -1.07014242

Intercepts:
    Value    Std. Error t value 
1|2  -2.5807   0.2975    -8.6748
2|3  -1.3068   0.3122    -4.1862
3|4   0.4677   0.3157     1.4815
4|5   1.9789   0.3225     6.1356
(657 observations deleted due to missingness)
olr_CRIT_IV2 olr_ACCESS_IV2 olr_CHECK_IV2 olr_TRUST_IV2
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
urbanicity 0.010*** 0.004* 0.005** 0.001
(0.002) (0.002) (0.002) (0.002)
PTYID_CV -0.194*** -0.232*** -0.302*** -0.449***
(0.018) (0.018) (0.019) (0.021)
LRSELF_CV -0.152*** -0.161*** -0.143*** -0.094***
(0.017) (0.015) (0.016) (0.021)
age_CV 0.011*** 0.007** 0.013*** 0.018***
(0.002) (0.003) (0.002) (0.002)
High school credential -0.270+ 0.137 0.004 -0.271
(0.138) (0.156) (0.175) (0.210)
Some post-high school, no bachelor's degree 0.110 0.486** 0.273+ -0.254
(0.152) (0.176) (0.142) (0.213)
Bachelor's degree 0.616*** 0.725*** 0.260 -0.179
(0.156) (0.175) (0.160) (0.213)
Graduate degree 0.750*** 0.908*** 0.386* -0.120
(0.162) (0.194) (0.176) (0.245)
income_CV 0.028*** 0.009 0.010+ 0.000
(0.005) (0.006) (0.006) (0.005)
Black, non-Hispanic -0.361** -0.589*** -0.380* 0.268+
(0.132) (0.137) (0.142) (0.155)
Hispanic -0.148 -0.106 -0.026 0.253*
(0.092) (0.105) (0.111) (0.124)
Asian/NHPI, non-Hispanic -0.193 -0.375* -0.231 0.429*
(0.202) (0.179) (0.175) (0.158)
NA/AN or other, non-Hispanic -0.142 -0.267 -0.090 0.273
(0.196) (0.341) (0.324) (0.242)
Multiple races, non-Hispanic -0.157 -0.224 -0.054 0.162
(0.154) (0.188) (0.258) (0.231)
Female -0.506*** -0.361*** -0.098 -0.062
(0.068) (0.060) (0.075) (0.058)
1|2 -2.521*** -2.940*** -2.581***
(0.237) (0.217) (0.297)
2|3 -1.837*** -2.059*** -1.307***
(0.231) (0.216) (0.312)
3|4 -0.470* -0.653** 0.468
(0.229) (0.207) (0.316)
4|5 0.569* 0.396+ 1.979***
(0.221) (0.209) (0.323)
1|1.66666666666667 -3.683***
(0.271)
1.66666666666667|2.33333333333333 -2.866***
(0.266)
2.33333333333333|3 -2.721***
(0.268)
3|3.66666666666667 -0.972***
(0.268)
3.66666666666667|4.33333333333333 -0.813**
(0.265)
4.33333333333333|5 0.061
(0.269)
Num.Obs. 6205 6200 6203 6214
RMSE 3.78 3.81 3.55 2.58

3.5.4.2 Odds Ratios

Characteristic OR 95% CI
urbanicity 1.01 1.01, 1.01
PTYID_CV 0.82 0.80, 0.85
LRSELF_CV 0.86 0.83, 0.89
age_CV 1.01 1.01, 1.02
education_CVfct

    Less than high school credential — —
    High school credential 0.76 0.58, 1.00
    Some post-high school, no bachelor's degree 1.12 0.83, 1.51
    Bachelor's degree 1.85 1.37, 2.51
    Graduate degree 2.12 1.54, 2.91
income_CV 1.03 1.02, 1.04
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 0.70 0.54, 0.90
    Hispanic 0.86 0.72, 1.03
    Asian/NHPI, non-Hispanic 0.82 0.56, 1.22
    NA/AN or other, non-Hispanic 0.87 0.59, 1.27
    Multiple races, non-Hispanic 0.85 0.63, 1.16
sex_CVfct

    Male — —
    Female 0.60 0.53, 0.69
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
Characteristic OR 95% CI
urbanicity 1.00 1.00, 1.01
PTYID_CV 0.79 0.77, 0.82
LRSELF_CV 0.85 0.83, 0.88
age_CV 1.01 1.00, 1.01
education_CVfct

    Less than high school credential — —
    High school credential 1.15 0.84, 1.56
    Some post-high school, no bachelor's degree 1.63 1.15, 2.29
    Bachelor's degree 2.07 1.47, 2.91
    Graduate degree 2.48 1.70, 3.62
income_CV 1.01 1.00, 1.02
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 0.55 0.42, 0.73
    Hispanic 0.90 0.73, 1.11
    Asian/NHPI, non-Hispanic 0.69 0.48, 0.98
    NA/AN or other, non-Hispanic 0.77 0.39, 1.49
    Multiple races, non-Hispanic 0.80 0.55, 1.15
sex_CVfct

    Male — —
    Female 0.70 0.62, 0.78
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
Characteristic OR 95% CI
urbanicity 1.01 1.00, 1.01
PTYID_CV 0.74 0.71, 0.77
LRSELF_CV 0.87 0.84, 0.89
age_CV 1.01 1.01, 1.02
education_CVfct

    Less than high school credential — —
    High school credential 1.00 0.71, 1.42
    Some post-high school, no bachelor's degree 1.31 0.99, 1.74
    Bachelor's degree 1.30 0.95, 1.77
    Graduate degree 1.47 1.04, 2.08
income_CV 1.01 1.00, 1.02
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 0.68 0.52, 0.90
    Hispanic 0.97 0.78, 1.21
    Asian/NHPI, non-Hispanic 0.79 0.56, 1.12
    NA/AN or other, non-Hispanic 0.91 0.48, 1.73
    Multiple races, non-Hispanic 0.95 0.57, 1.57
sex_CVfct

    Male — —
    Female 0.91 0.78, 1.05
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
Characteristic OR 95% CI
urbanicity 1.00 1.00, 1.00
PTYID_CV 0.64 0.61, 0.67
LRSELF_CV 0.91 0.87, 0.95
age_CV 1.02 1.01, 1.02
education_CVfct

    Less than high school credential — —
    High school credential 0.76 0.51, 1.15
    Some post-high school, no bachelor's degree 0.78 0.51, 1.18
    Bachelor's degree 0.84 0.55, 1.27
    Graduate degree 0.89 0.55, 1.43
income_CV 1.00 0.99, 1.01
race_CVfct

    White, non-Hispanic — —
    Black, non-Hispanic 1.31 0.96, 1.77
    Hispanic 1.29 1.01, 1.64
    Asian/NHPI, non-Hispanic 1.54 1.13, 2.09
    NA/AN or other, non-Hispanic 1.31 0.82, 2.11
    Multiple races, non-Hispanic 1.18 0.75, 1.85
sex_CVfct

    Male — —
    Female 0.94 0.84, 1.05
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
term olr_CRIT_IV2 olr_ACCESS_IV2 olr_CHECK_IV2 olr_TRUST_IV2
urbanicity 1.01  1.004 1.005 1.001
PTYID_CV 0.824 0.793 0.739 0.638
LRSELF_CV 0.859 0.851 0.867 0.91 
age_CV 1.012 1.007 1.013 1.018
High school credential 0.763 1.147 1.004 0.763
Some post-high school, no bachelor's degree 1.116 1.625 1.314 0.776
Bachelor's degree 1.852 2.066 1.297 0.836
Graduate degree 2.117 2.478 1.471 0.887
income_CV 1.028 1.009 1.01  1    
Black, non-Hispanic 0.697 0.555 0.684 1.307
Hispanic 0.862 0.9   0.974 1.288
Asian/NHPI, non-Hispanic 0.825 0.687 0.794 1.535
NA/AN or other, non-Hispanic 0.868 0.765 0.914 1.314
Multiple races, non-Hispanic 0.855 0.799 0.947 1.176
Female 0.603 0.697 0.907 0.94 
1|2 0.08  NA 0.053 0.076
2|3 0.159 NA 0.128 0.271
3|4 0.625 NA 0.52  1.596
4|5 1.767 NA 1.485 7.234
1|1.66666666666667 NA 0.025 NA NA
1.66666666666667|2.33333333333333 NA 0.057 NA NA
2.33333333333333|3 NA 0.066 NA NA
3|3.66666666666667 NA 0.379 NA NA
3.66666666666667|4.33333333333333 NA 0.443 NA NA
4.33333333333333|5 NA 1.062 NA NA

3.5.4.3 Plots

3.6 Comparing Urbanicity and Identity

Rural vs. Urban

Urbanicity

urban_fct p p_se p_low p_upp
0  0.104 0.006 0.093 0.116
1  0.896 0.006 0.884 0.907

Identity

PLACEID_fct p p_se p_low p_upp
rural 0.431 0.009 0.414 0.448
urban 0.55  0.008 0.533 0.567
NA 0.019 0.002 0.015 0.023

Urbanicity

variable corr corr_se corr_low corr_upp
CRIT 0.152 0.016 0.118 0.185
ACCESS 0.105 0.017 0.071 0.139
CHECK 0.114 0.014 0.087 0.142
TRUST 0.105 0.016 0.074 0.136

Identity

variable corr corr_se corr_low corr_upp
CRIT 0.164 0.02  0.124 0.205
ACCESS 0.146 0.018 0.111 0.182
CHECK 0.118 0.018 0.082 0.155
TRUST 0.179 0.018 0.143 0.215

3.6.1 Regression

3.6.1.1 Models

(1) = Urbanicity

(2) = Urban-Rural Identity

(1) (2)
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
urbanicity 0.010*** 0.010***
(0.002) (0.002)
PTYID_CV -0.194*** -0.194***
(0.018) (0.018)
LRSELF_CV -0.152*** -0.152***
(0.017) (0.017)
age_CV 0.011*** 0.011***
(0.002) (0.002)
High school credential -0.270+ -0.270+
(0.138) (0.138)
Some post-high school, no bachelor's degree 0.110 0.110
(0.152) (0.152)
Bachelor's degree 0.616*** 0.616***
(0.156) (0.156)
Graduate degree 0.750*** 0.750***
(0.162) (0.162)
income_CV 0.028*** 0.028***
(0.005) (0.005)
Black, non-Hispanic -0.361** -0.361**
(0.132) (0.132)
Hispanic -0.148 -0.148
(0.092) (0.092)
Asian/NHPI, non-Hispanic -0.193 -0.193
(0.202) (0.202)
NA/AN or other, non-Hispanic -0.142 -0.142
(0.196) (0.196)
Multiple races, non-Hispanic -0.157 -0.157
(0.154) (0.154)
Female -0.506*** -0.506***
(0.068) (0.068)
1|2 -2.521*** -2.521***
(0.237) (0.237)
2|3 -1.837*** -1.837***
(0.231) (0.231)
3|4 -0.470* -0.470*
(0.229) (0.229)
4|5 0.569* 0.569*
(0.221) (0.221)
Num.Obs. 6205 6205
RMSE 3.78 3.78
(1) (2)
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
urbanicity 0.004* 0.004*
(0.002) (0.002)
PTYID_CV -0.232*** -0.232***
(0.018) (0.018)
LRSELF_CV -0.161*** -0.161***
(0.015) (0.015)
age_CV 0.007** 0.007**
(0.003) (0.003)
High school credential 0.137 0.137
(0.156) (0.156)
Some post-high school, no bachelor's degree 0.486** 0.486**
(0.176) (0.176)
Bachelor's degree 0.725*** 0.725***
(0.175) (0.175)
Graduate degree 0.908*** 0.908***
(0.194) (0.194)
income_CV 0.009 0.009
(0.006) (0.006)
Black, non-Hispanic -0.589*** -0.589***
(0.137) (0.137)
Hispanic -0.106 -0.106
(0.105) (0.105)
Asian/NHPI, non-Hispanic -0.375* -0.375*
(0.179) (0.179)
NA/AN or other, non-Hispanic -0.267 -0.267
(0.341) (0.341)
Multiple races, non-Hispanic -0.224 -0.224
(0.188) (0.188)
Female -0.361*** -0.361***
(0.060) (0.060)
1|1.66666666666667 -3.683*** -3.683***
(0.271) (0.271)
1.66666666666667|2.33333333333333 -2.866*** -2.866***
(0.266) (0.266)
2.33333333333333|3 -2.721*** -2.721***
(0.268) (0.268)
3|3.66666666666667 -0.972*** -0.972***
(0.268) (0.268)
3.66666666666667|4.33333333333333 -0.813** -0.813**
(0.265) (0.265)
4.33333333333333|5 0.061 0.061
(0.269) (0.269)
Num.Obs. 6200 6200
RMSE 3.81 3.81
(1) (2)
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
urbanicity 0.005** 0.005**
(0.002) (0.002)
PTYID_CV -0.302*** -0.302***
(0.019) (0.019)
LRSELF_CV -0.143*** -0.143***
(0.016) (0.016)
age_CV 0.013*** 0.013***
(0.002) (0.002)
High school credential 0.004 0.004
(0.175) (0.175)
Some post-high school, no bachelor's degree 0.273+ 0.273+
(0.142) (0.142)
Bachelor's degree 0.260 0.260
(0.160) (0.160)
Graduate degree 0.386* 0.386*
(0.176) (0.176)
income_CV 0.010+ 0.010+
(0.006) (0.006)
Black, non-Hispanic -0.380* -0.380*
(0.142) (0.142)
Hispanic -0.026 -0.026
(0.111) (0.111)
Asian/NHPI, non-Hispanic -0.231 -0.231
(0.175) (0.175)
NA/AN or other, non-Hispanic -0.090 -0.090
(0.324) (0.324)
Multiple races, non-Hispanic -0.054 -0.054
(0.258) (0.258)
Female -0.098 -0.098
(0.075) (0.075)
1|2 -2.940*** -2.940***
(0.217) (0.217)
2|3 -2.059*** -2.059***
(0.216) (0.216)
3|4 -0.653** -0.653**
(0.207) (0.207)
4|5 0.396+ 0.396+
(0.209) (0.209)
Num.Obs. 6203 6203
RMSE 3.55 3.55
(1) (2)
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
urbanicity 0.001 0.001
(0.002) (0.002)
PTYID_CV -0.449*** -0.449***
(0.021) (0.021)
LRSELF_CV -0.094*** -0.094***
(0.021) (0.021)
age_CV 0.018*** 0.018***
(0.002) (0.002)
High school credential -0.271 -0.271
(0.210) (0.210)
Some post-high school, no bachelor's degree -0.254 -0.254
(0.213) (0.213)
Bachelor's degree -0.179 -0.179
(0.213) (0.213)
Graduate degree -0.120 -0.120
(0.245) (0.245)
income_CV 0.000 0.000
(0.005) (0.005)
Black, non-Hispanic 0.268+ 0.268+
(0.155) (0.155)
Hispanic 0.253* 0.253*
(0.124) (0.124)
Asian/NHPI, non-Hispanic 0.429* 0.429*
(0.158) (0.158)
NA/AN or other, non-Hispanic 0.273 0.273
(0.242) (0.242)
Multiple races, non-Hispanic 0.162 0.162
(0.231) (0.231)
Female -0.062 -0.062
(0.058) (0.058)
1|2 -2.581*** -2.581***
(0.297) (0.297)
2|3 -1.307*** -1.307***
(0.312) (0.312)
3|4 0.468 0.468
(0.316) (0.316)
4|5 1.979*** 1.979***
(0.323) (0.323)
Num.Obs. 6214 6214
RMSE 2.58 2.58

3.6.1.2 Odds Ratios

term olr_CRIT_IV1 olr_CRIT_IV2
urbanicity 1.01  1.01 
PTYID_CV 0.824 0.824
LRSELF_CV 0.859 0.859
age_CV 1.012 1.012
High school credential 0.763 0.763
Some post-high school, no bachelor's degree 1.116 1.116
Bachelor's degree 1.852 1.852
Graduate degree 2.117 2.117
income_CV 1.028 1.028
Black, non-Hispanic 0.697 0.697
Hispanic 0.862 0.862
Asian/NHPI, non-Hispanic 0.825 0.825
NA/AN or other, non-Hispanic 0.868 0.868
Multiple races, non-Hispanic 0.855 0.855
Female 0.603 0.603
1|2 0.08  0.08 
2|3 0.159 0.159
3|4 0.625 0.625
4|5 1.767 1.767
term olr_ACCESS_IV1 olr_ACCESS_IV2
urbanicity 1.004 1.004
PTYID_CV 0.793 0.793
LRSELF_CV 0.851 0.851
age_CV 1.007 1.007
High school credential 1.147 1.147
Some post-high school, no bachelor's degree 1.625 1.625
Bachelor's degree 2.066 2.066
Graduate degree 2.478 2.478
income_CV 1.009 1.009
Black, non-Hispanic 0.555 0.555
Hispanic 0.9   0.9  
Asian/NHPI, non-Hispanic 0.687 0.687
NA/AN or other, non-Hispanic 0.765 0.765
Multiple races, non-Hispanic 0.799 0.799
Female 0.697 0.697
1|1.66666666666667 0.025 0.025
1.66666666666667|2.33333333333333 0.057 0.057
2.33333333333333|3 0.066 0.066
3|3.66666666666667 0.379 0.379
3.66666666666667|4.33333333333333 0.443 0.443
4.33333333333333|5 1.062 1.062
term olr_CHECK_IV1 olr_CHECK_IV2
urbanicity 1.005 1.005
PTYID_CV 0.739 0.739
LRSELF_CV 0.867 0.867
age_CV 1.013 1.013
High school credential 1.004 1.004
Some post-high school, no bachelor's degree 1.314 1.314
Bachelor's degree 1.297 1.297
Graduate degree 1.471 1.471
income_CV 1.01  1.01 
Black, non-Hispanic 0.684 0.684
Hispanic 0.974 0.974
Asian/NHPI, non-Hispanic 0.794 0.794
NA/AN or other, non-Hispanic 0.914 0.914
Multiple races, non-Hispanic 0.947 0.947
Female 0.907 0.907
1|2 0.053 0.053
2|3 0.128 0.128
3|4 0.52  0.52 
4|5 1.485 1.485
term olr_TRUST_IV1 olr_TRUST_IV2
urbanicity 1.001 1.001
PTYID_CV 0.638 0.638
LRSELF_CV 0.91  0.91 
age_CV 1.018 1.018
High school credential 0.763 0.763
Some post-high school, no bachelor's degree 0.776 0.776
Bachelor's degree 0.836 0.836
Graduate degree 0.887 0.887
income_CV 1     1    
Black, non-Hispanic 1.307 1.307
Hispanic 1.288 1.288
Asian/NHPI, non-Hispanic 1.535 1.535
NA/AN or other, non-Hispanic 1.314 1.314
Multiple races, non-Hispanic 1.176 1.176
Female 0.94  0.94 
1|2 0.076 0.076
2|3 0.271 0.271
3|4 1.596 1.596
4|5 7.234 7.234
term olr_CRIT_IV1 olr_CRIT_IV2 olr_ACCESS_IV1 olr_ACCESS_IV2 olr_CHECK_IV1 olr_CHECK_IV2 olr_TRUST_IV1 olr_TRUST_IV2
urbanicity 1.01  1.01  1.004 1.004 1.005 1.005 1.001 1.001
PTYID_CV 0.824 0.824 0.793 0.793 0.739 0.739 0.638 0.638
LRSELF_CV 0.859 0.859 0.851 0.851 0.867 0.867 0.91  0.91 
age_CV 1.012 1.012 1.007 1.007 1.013 1.013 1.018 1.018
High school credential 0.763 0.763 1.147 1.147 1.004 1.004 0.763 0.763
Some post-high school, no bachelor's degree 1.116 1.116 1.625 1.625 1.314 1.314 0.776 0.776
Bachelor's degree 1.852 1.852 2.066 2.066 1.297 1.297 0.836 0.836
Graduate degree 2.117 2.117 2.478 2.478 1.471 1.471 0.887 0.887
income_CV 1.028 1.028 1.009 1.009 1.01  1.01  1     1    
Black, non-Hispanic 0.697 0.697 0.555 0.555 0.684 0.684 1.307 1.307
Hispanic 0.862 0.862 0.9   0.9   0.974 0.974 1.288 1.288
Asian/NHPI, non-Hispanic 0.825 0.825 0.687 0.687 0.794 0.794 1.535 1.535
NA/AN or other, non-Hispanic 0.868 0.868 0.765 0.765 0.914 0.914 1.314 1.314
Multiple races, non-Hispanic 0.855 0.855 0.799 0.799 0.947 0.947 1.176 1.176
Female 0.603 0.603 0.697 0.697 0.907 0.907 0.94  0.94 
1|2 0.08  0.08  NA NA 0.053 0.053 0.076 0.076
2|3 0.159 0.159 NA NA 0.128 0.128 0.271 0.271
3|4 0.625 0.625 NA NA 0.52  0.52  1.596 1.596
4|5 1.767 1.767 NA NA 1.485 1.485 7.234 7.234
1|1.66666666666667 NA NA 0.025 0.025 NA NA NA NA
1.66666666666667|2.33333333333333 NA NA 0.057 0.057 NA NA NA NA
2.33333333333333|3 NA NA 0.066 0.066 NA NA NA NA
3|3.66666666666667 NA NA 0.379 0.379 NA NA NA NA
3.66666666666667|4.33333333333333 NA NA 0.443 0.443 NA NA NA NA
4.33333333333333|5 NA NA 1.062 1.062 NA NA NA NA

3.6.1.3 Plots