DSU EDA Analysis

Author

Charles Rose

Exploratory Data Analysis of ABFM and Missing Data

The EDA presented will produce descriptive tables by three variables. These variables are: outcome screening, missing race (yes, no), and missing ethnicity *yes, no).

Load Libraries

Load Final Analysis Dataset

[1] "C:/GitLab Repository/inquisitiveimputers/R code"

Create Desctiptive Tables for Screening for Variables of Interest

[1] 210888
Warning: There was 1 warning in `mutate()`.
ℹ In argument: `tract_na = fct_relevel(tract_na, "Yes", "Missing")`.
Caused by warning:
! 1 unknown level in `f`: Missing
# A tibble: 6 × 146
  patientuid       gender race  hispanic dob   outcome tract county_fips zipcode
  <chr>            <fct>  <chr> <chr>    <chr> <chr>   <chr> <chr>       <chr>  
1 3a336c26-5e1c-4… Male   White <NA>     2020… 1       3110… 31109       68521  
2 3a336c26-5e1c-4… Male   White <NA>     2020… 1       3110… 31109       68521  
3 3a336c26-5e1c-4… Male   White <NA>     2020… 1       3110… 31109       68521  
4 3a336c26-5e1c-4… Male   White <NA>     2020… 1       3110… 31109       68521  
5 3a336c26-5e1c-4… Male   White <NA>     2020… 1       3110… 31109       68521  
6 3a336c26-5e1c-4… Male   White <NA>     2020… 1       3110… 31109       68521  
# ℹ 137 more variables: USPS_ZIP_PREF_STATE <chr>, reweight_t <chr>,
#   weight_t <dbl>, weight_c <dbl>, missing_geography <chr>, stcnty_c <chr>,
#   rpl_theme1_c <dbl>, rpl_theme2_c <dbl>, rpl_theme3_c <dbl>,
#   rpl_theme4_c <dbl>, rpl_themes_c <dbl>, area_sqmi_c <dbl>,
#   e_totpop_c <dbl>, d_pop_c <dbl>, st_abbr_t <chr>, rpl_theme1_t <dbl>,
#   rpl_theme2_t <dbl>, rpl_theme3_t <dbl>, rpl_theme4_t <dbl>,
#   rpl_themes_t <dbl>, area_sqmi_t <dbl>, e_totpop_t <dbl>, d_pop_t <dbl>, …

East North Central East South Central    Middle Atlantic           Mountain 
             60711              10367               9177              17484 
       New England            Pacific     South Atlantic West North Central 
              8505               5503              84437             245351 
West South Central 
            119490

Tables for Missing Data by Outcome Screening and Record

Table 1A: ABFM Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Developmental Screening p-value2
No, n = 489,0471 Yes, n = 216,7531
Gender


<0.001
    Female 340,417 (48%) 234,674 (48%) 105,743 (49%)
    Male 364,751 (52%) 253,876 (52%) 110,875 (51%)
    Unknown 632 497 135
race


<0.001
    AIAN 18,015 (4.4%) 17,111 (6.0%) 904 (0.7%)
    Asian 11,412 (2.8%) 8,159 (2.8%) 3,253 (2.6%)
    Black 50,872 (12%) 34,838 (12%) 16,034 (13%)
    Multiple 3,469 (0.8%) 1,583 (0.6%) 1,886 (1.5%)
    NHOPI 1,382 (0.3%) 1,044 (0.4%) 338 (0.3%)
    White 327,530 (79%) 224,267 (78%) 103,263 (82%)
    Unknown 293,120 202,045 91,075
hispanic


<0.001
    No 297,790 (69%) 216,416 (72%) 81,374 (62%)
    Yes 134,050 (31%) 83,417 (28%) 50,633 (38%)
    Unknown 273,960 189,214 84,746
SVI_CT 0.51 (0.29) 0.51 (0.28) 0.50 (0.31) 0.008
    Unknown 108,669 72,837 35,832
ADI_CT 58.74 (25.18) 60.54 (24.98) 54.60 (25.15) <0.001
    Unknown 108,669 72,837 35,832
SDI_CT 16.10 (8.78) 16.26 (8.58) 15.72 (9.22) <0.001
    Unknown 108,692 72,858 35,834
NSS7_CT -0.06 (0.87) -0.04 (0.84) -0.11 (0.92) <0.001
    Unknown 108,692 72,858 35,834
FDep_CT -0.18 (1.39) -0.24 (1.34) -0.02 (1.49) <0.001
    Unknown 108,669 72,837 35,832
ICE_BW_CT 0.57 (0.37) 0.58 (0.37) 0.55 (0.37) <0.001
    Unknown 108,669 72,837 35,832
ICE_INC_CT -0.13 (0.31) -0.14 (0.31) -0.08 (0.33) <0.001
    Unknown 108,669 72,837 35,832
ICE_INC_BW_CT 0.15 (0.21) 0.15 (0.20) 0.17 (0.22) <0.001
    Unknown 108,669 72,837 35,832
ICE_INC_WNH_CT 0.06 (0.28) 0.06 (0.27) 0.07 (0.31) <0.001
    Unknown 108,669 72,837 35,832
ICE_WNH_CT 0.30 (0.57) 0.32 (0.56) 0.26 (0.60) <0.001
    Unknown 108,669 72,837 35,832
SVI_C 0.61 (0.25) 0.61 (0.25) 0.61 (0.25) <0.001
    Unknown 108,669 72,837 35,832
ADI_C 33.61 (25.32) 35.58 (25.57) 29.07 (24.15) <0.001
    Unknown 108,669 72,837 35,832
SDI_C 24.82 (7.72) 25.18 (7.49) 23.99 (8.16) <0.001
    Unknown 108,669 72,837 35,832
NSS7_C -0.17 (0.64) -0.15 (0.62) -0.23 (0.69) <0.001
    Unknown 108,669 72,837 35,832
FDep_C -0.62 (1.31) -0.51 (1.29) -0.88 (1.33) <0.001
    Unknown 108,669 72,837 35,832
ICE_BW_C 0.59 (0.26) 0.59 (0.26) 0.57 (0.26) <0.001
    Unknown 108,669 72,837 35,832
ICE_INC_C -0.13 (0.15) -0.14 (0.15) -0.10 (0.14) <0.001
    Unknown 108,669 72,837 35,832
ICE_INC_BW_C 0.16 (0.10) 0.16 (0.10) 0.17 (0.10) <0.001
    Unknown 108,669 72,837 35,832
ICE_INC_WNH_C 0.08 (0.16) 0.07 (0.15) 0.08 (0.18) <0.001
    Unknown 108,669 72,837 35,832
ICE_WNH_C 0.34 (0.42) 0.35 (0.42) 0.31 (0.44) <0.001
    Unknown 108,669 72,837 35,832
1 n (%); Mean (SD)
2 Pearson’s Chi-squared test; Wilcoxon rank sum test
Table 1B: ACS Census Tract Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Developmental Screening p-value2
No, n = 489,0471 Yes, n = 216,7531
acs_avg_hh_size_t 2.68 (0.54) 2.67 (0.54) 2.69 (0.53) <0.001
    Unknown 4,399 3,032 1,367
acs_pct_child_disab_t 4.58 (4.54) 4.68 (4.63) 4.37 (4.34) <0.001
    Unknown 4,681 3,228 1,453
acs_pct_ctz_naturalized_t 4.67 (5.76) 4.45 (5.68) 5.19 (5.91) <0.001
    Unknown 1,078 710 368
acs_pct_ctz_nonus_born_t 5.47 (6.13) 5.24 (6.05) 6.01 (6.29) <0.001
    Unknown 1,078 710 368
acs_pct_ctz_us_born_t 88.66 (12.14) 89.19 (11.92) 87.46 (12.53) <0.001
    Unknown 1,078 710 368
acs_pct_foreign_born_t 11.34 (12.14) 10.81 (11.92) 12.54 (12.53) <0.001
    Unknown 1,078 710 368
acs_pct_non_citizen_t 5.87 (7.73) 5.57 (7.62) 6.53 (7.94) <0.001
    Unknown 1,078 710 368
acs_pct_api_lang_t 2.05 (4.05) 2.03 (4.09) 2.10 (3.97) <0.001
    Unknown 1,078 710 368
acs_pct_english_t 79.99 (23.18) 81.08 (22.30) 77.51 (24.88) <0.001
    Unknown 1,078 710 368
acs_pct_spanish_t 14.84 (21.95) 13.59 (20.74) 17.66 (24.22) <0.001
    Unknown 1,078 710 368
acs_pct_hh_no_internet_t 13.66 (10.16) 14.23 (10.26) 12.38 (9.83) <0.001
    Unknown 4,029 2,722 1,307
acs_pct_child_1fam_t 29.67 (19.23) 29.91 (19.25) 29.12 (19.19) <0.001
    Unknown 5,419 3,885 1,534
acs_pct_children_grandparent_t 7.95 (8.27) 8.12 (8.35) 7.57 (8.05) <0.001
    Unknown 3,892 2,705 1,187
acs_pct_hh_kid_1prnt_t 16.96 (9.38) 16.95 (9.16) 17.00 (9.87) <0.001
    Unknown 4,029 2,722 1,307
acs_pct_not_labor_t 36.03 (10.94) 36.72 (10.98) 34.47 (10.68) <0.001
    Unknown 1,078 710 368
acs_pct_unemploy_t 4.93 (4.11) 5.01 (4.10) 4.74 (4.12) <0.001
    Unknown 3,829 2,551 1,278
acs_gini_index_t 0.41 (0.06) 0.41 (0.06) 0.41 (0.06) <0.001
    Unknown 4,342 2,941 1,401
acs_median_hh_inc_t 64,069.54 (26,107.45) 62,832.14 (25,682.00) 66,865.84 (26,834.96) <0.001
    Unknown 6,682 4,394 2,288
acs_pct_health_inc_below137_t 20.68 (13.32) 21.19 (13.24) 19.53 (13.44) <0.001
    Unknown 3,981 2,681 1,300
acs_pct_inc50_t 5.84 (5.53) 5.98 (5.60) 5.52 (5.34) <0.001
    Unknown 3,981 2,681 1,300
acs_pct_hh_food_stmp_t 11.36 (10.41) 11.43 (10.04) 11.19 (11.20) <0.001
    Unknown 4,029 2,722 1,307
acs_pct_bachelor_dgr_t 18.12 (9.80) 17.48 (9.54) 19.56 (10.22) <0.001
    Unknown 1,102 729 373
acs_pct_owner_hu_t 65.81 (20.78) 66.05 (20.65) 65.27 (21.07) <0.001
    Unknown 4,029 2,722 1,307
acs_pct_vacant_hu_t 10.02 (8.57) 10.65 (8.90) 8.59 (7.59) <0.001
    Unknown 4,029 2,722 1,307
acs_pct_hu_no_veh_t 5.93 (7.21) 5.98 (7.32) 5.81 (6.94) <0.001
    Unknown 4,029 2,722 1,307
acs_pct_medicaid_any_below64_t 17.63 (12.94) 18.21 (12.84) 16.33 (13.07) <0.001
    Unknown 3,649 2,373 1,276
acs_pct_uninsured_below64_t 12.26 (9.34) 12.38 (9.41) 11.98 (9.15) <0.001
    Unknown 3,649 2,373 1,276
1 Mean (SD)
2 Wilcoxon rank sum test
Table 1C: ACS County Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Developmental Screening p-value2
No, n = 489,0471 Yes, n = 216,7531
acs_avg_hh_size_c 2.59 (0.29) 2.59 (0.28) 2.59 (0.29) <0.001
acs_pct_child_disab_c 4.55 (1.42) 4.63 (1.51) 4.38 (1.18) <0.001
acs_pct_ctz_us_born_c 89.00 (8.47) 89.47 (8.62) 87.95 (8.01) <0.001
acs_pct_ctz_nonus_born_c 5.32 (4.21) 5.12 (4.32) 5.77 (3.91) <0.001
acs_pct_foreign_born_c 11.00 (8.47) 10.53 (8.62) 12.05 (8.01) <0.001
acs_pct_non_citizen_c 5.68 (4.78) 5.41 (4.79) 6.27 (4.68) <0.001
acs_pct_ctz_naturalized_c 4.51 (3.98) 4.32 (4.08) 4.94 (3.71) <0.001
acs_pct_api_lang_c 2.07 (2.16) 2.02 (2.24) 2.19 (1.97) <0.001
acs_pct_english_c 81.23 (17.80) 82.08 (17.19) 79.31 (18.97) <0.001
acs_pct_spanish_c 13.36 (16.95) 12.53 (15.97) 15.24 (18.85) <0.001
acs_pct_child_1fam_c 29.35 (7.61) 29.58 (7.76) 28.84 (7.21) <0.001
acs_pct_children_grandparent_c 7.74 (3.28) 7.91 (3.38) 7.34 (3.01) <0.001
acs_pct_hh_kid_1prnt_c 16.55 (3.88) 16.58 (3.84) 16.49 (3.97) <0.001
acs_pct_hh_no_internet_c 13.14 (6.27) 13.69 (6.50) 11.90 (5.54) <0.001
acs_pct_unemploy_c 4.90 (1.63) 4.97 (1.66) 4.75 (1.55) <0.001
acs_pct_not_labor_c 36.52 (6.81) 37.17 (6.93) 35.04 (6.28) <0.001
acs_gini_index_c 0.45 (0.03) 0.45 (0.03) 0.46 (0.03) <0.001
acs_median_hh_inc_c 60,191.18 (11,660.17) 59,477.46 (11,889.88) 61,801.50 (10,955.03) <0.001
    Unknown 4 4 0
acs_pct_health_inc_below137_c 20.62 (6.00) 20.93 (5.88) 19.94 (6.21) <0.001
acs_pct_inc50_c 5.95 (2.03) 5.99 (2.03) 5.85 (2.03) <0.001
acs_pct_hh_food_stmp_c 10.89 (4.85) 10.95 (4.66) 10.75 (5.25) <0.001
acs_pct_bachelor_dgr_c 18.69 (5.83) 18.11 (5.89) 20.02 (5.48) <0.001
acs_pct_owner_hu_c 65.29 (8.14) 65.67 (8.35) 64.44 (7.59) <0.001
acs_pct_vacant_hu_c 10.80 (6.56) 11.42 (6.78) 9.43 (5.78) <0.001
acs_pct_hu_no_veh_c 5.93 (3.35) 5.95 (3.50) 5.89 (2.99) <0.001
acs_pct_medicaid_any_below64_c 17.40 (7.25) 17.96 (7.43) 16.12 (6.64) <0.001
acs_pct_uninsured_below64_c 12.29 (6.56) 12.27 (6.55) 12.32 (6.59) 0.2
1 Mean (SD)
2 Wilcoxon rank sum test
Table 1D: SVI by County and Tract Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Developmental Screening p-value2
No, n = 489,0471 Yes, n = 216,7531
rpl_theme1_c 0.52 (0.26) 0.54 (0.26) 0.50 (0.26) <0.001
rpl_theme2_c 0.53 (0.28) 0.54 (0.28) 0.51 (0.27) <0.001
rpl_theme3_c 0.65 (0.22) 0.65 (0.23) 0.67 (0.20) <0.001
rpl_theme4_c 0.62 (0.22) 0.62 (0.22) 0.63 (0.20) <0.001
rpl_themes_c 0.59 (0.25) 0.59 (0.25) 0.57 (0.24) <0.001
area_sqmi_c 1,243.95 (1,477.66) 1,291.34 (1,571.42) 1,137.00 (1,233.70) <0.001
rpl_theme1_t 0.50 (0.29) 0.51 (0.29) 0.48 (0.31) <0.001
    Unknown 3,868 2,581 1,287
rpl_theme2_t 0.54 (0.28) 0.54 (0.28) 0.54 (0.28) <0.001
    Unknown 3,645 2,373 1,272
rpl_theme3_t 0.46 (0.28) 0.45 (0.28) 0.48 (0.28) <0.001
    Unknown 1,078 710 368
rpl_theme4_t 0.51 (0.28) 0.52 (0.28) 0.50 (0.28) <0.001
    Unknown 4,029 2,722 1,307
rpl_themes_t 0.52 (0.29) 0.52 (0.29) 0.50 (0.30) <0.001
    Unknown 4,228 2,912 1,316
area_sqmi_t 56.20 (252.12) 64.80 (286.82) 36.79 (144.32) <0.001
1 Mean (SD)
2 Wilcoxon rank sum test
Table 1E: COI Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Developmental Screening p-value2
No, n = 489,0471 Yes, n = 216,7531
r_ED_nat_t 47.40 (25.39) 46.14 (25.20) 50.32 (25.60) <0.001
    Unknown 185,374 125,038 60,336
r_HE_nat_t 44.33 (27.43) 42.70 (27.39) 48.12 (27.13) <0.001
    Unknown 185,369 125,035 60,334
r_SE_nat_t 42.73 (25.32) 41.38 (24.77) 45.87 (26.29) <0.001
    Unknown 185,544 125,164 60,380
r_COI_nat_t 43.76 (25.68) 42.30 (25.26) 47.17 (26.31) <0.001
    Unknown 185,372 125,038 60,334
1 Mean (SD)
2 Wilcoxon rank sum test
Table 1F: Percent Race, Ethnicity, Gender Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Developmental Screening p-value2
No, n = 489,0471 Yes, n = 216,7531
percent_male_t 49.63 (5.18) 49.66 (5.15) 49.56 (5.24) <0.001
    Unknown 1,078 710 368
percent_female_t 50.37 (5.18) 50.34 (5.15) 50.44 (5.24) <0.001
    Unknown 1,078 710 368
percent_hispanic_t 19.75 (25.43) 18.35 (24.25) 22.93 (27.64) <0.001
    Unknown 1,078 710 368
percent_white_t 81.13 (17.89) 80.85 (18.25) 81.79 (17.00) <0.001
    Unknown 1,125 736 389
percent_black_t 8.82 (15.71) 8.93 (16.07) 8.57 (14.87) 0.6
    Unknown 1,125 736 389
percent_aian_t 1.13 (3.43) 1.37 (3.97) 0.60 (1.50) <0.001
    Unknown 1,125 736 389
percent_asian_t 3.28 (6.32) 3.25 (6.41) 3.34 (6.12) <0.001
    Unknown 1,125 736 389
percent_nhopi_t 0.16 (0.80) 0.16 (0.86) 0.15 (0.63) 0.7
    Unknown 1,125 736 389
percent_multi_t 5.48 (5.39) 5.45 (5.27) 5.55 (5.65) 0.015
    Unknown 1,125 736 389
percent_male_c 49.71 (1.48) 49.72 (1.54) 49.69 (1.35) <0.001
percent_female_c 50.29 (1.48) 50.28 (1.54) 50.31 (1.35) <0.001
percent_hispanic_c 18.30 (20.16) 17.36 (19.39) 20.43 (21.63) <0.001
percent_white_c 81.38 (11.66) 81.11 (12.08) 82.01 (10.65) <0.001
percent_black_c 8.76 (10.64) 8.84 (10.96) 8.58 (9.87) <0.001
percent_aian_c 1.14 (2.96) 1.37 (3.47) 0.63 (0.99) <0.001
percent_asian_c 3.23 (3.64) 3.17 (3.78) 3.37 (3.30) <0.001
percent_nhopi_c 0.15 (0.40) 0.15 (0.46) 0.13 (0.18) <0.001
percent_multi_c 5.33 (2.89) 5.35 (3.00) 5.29 (2.63) <0.001
1 Mean (SD)
2 Wilcoxon rank sum test

Descriptive Tables for Missing Race by Patient

Table 2A: ABFM Missing Race Descriptive Statistics Using Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Race p-value2
No, n = 412,6801 Yes, n = 293,1201
Screen Test


<0.001
    No 489,047 (69%) 287,002 (70%) 202,045 (69%)
    Yes 216,753 (31%) 125,678 (30%) 91,075 (31%)
Gender


0.075
    Female 340,417 (48%) 199,493 (48%) 140,924 (48%)
    Male 364,751 (52%) 212,991 (52%) 151,760 (52%)
    Unknown 632 196 436
hispanic


<0.001
    No 297,790 (69%) 266,803 (79%) 30,987 (32%)
    Yes 134,050 (31%) 69,100 (21%) 64,950 (68%)
    Unknown 273,960 76,777 197,183
1 n (%)
2 Pearson’s Chi-squared test
Table 2B: Missing Race ACS Census Tract Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Race p-value2
No, n = 412,6801 Yes, n = 293,1201
acs_avg_hh_size_t 2.68 (0.54) 2.66 (0.51) 2.70 (0.57) <0.001
    Unknown 4,399 2,281 2,118
acs_pct_child_disab_t 4.58 (4.54) 4.73 (4.67) 4.38 (4.35) <0.001
    Unknown 4,681 2,502 2,179
acs_pct_ctz_naturalized_t 4.67 (5.76) 4.41 (5.76) 5.05 (5.74) <0.001
    Unknown 1,078 650 428
acs_pct_ctz_nonus_born_t 5.47 (6.13) 5.24 (6.17) 5.81 (6.07) <0.001
    Unknown 1,078 650 428
acs_pct_ctz_us_born_t 88.66 (12.14) 89.40 (11.78) 87.61 (12.56) <0.001
    Unknown 1,078 650 428
acs_pct_foreign_born_t 11.34 (12.14) 10.60 (11.78) 12.39 (12.56) <0.001
    Unknown 1,078 650 428
acs_pct_non_citizen_t 5.87 (7.73) 5.36 (7.25) 6.58 (8.31) <0.001
    Unknown 1,078 650 428
acs_pct_api_lang_t 2.05 (4.05) 1.92 (4.15) 2.24 (3.89) <0.001
    Unknown 1,078 650 428
acs_pct_english_t 79.99 (23.18) 81.24 (22.39) 78.22 (24.15) <0.001
    Unknown 1,078 650 428
acs_pct_spanish_t 14.84 (21.95) 13.89 (20.99) 16.17 (23.16) <0.001
    Unknown 1,078 650 428
acs_pct_hh_no_internet_t 13.66 (10.16) 14.47 (10.32) 12.53 (9.83) <0.001
    Unknown 4,029 2,049 1,980
acs_pct_child_1fam_t 29.67 (19.23) 30.33 (19.62) 28.74 (18.63) <0.001
    Unknown 5,419 2,834 2,585
acs_pct_children_grandparent_t 7.95 (8.27) 8.34 (8.44) 7.41 (7.99) <0.001
    Unknown 3,892 2,105 1,787
acs_pct_hh_kid_1prnt_t 16.96 (9.38) 17.18 (9.28) 16.65 (9.51) <0.001
    Unknown 4,029 2,049 1,980
acs_pct_not_labor_t 36.03 (10.94) 37.09 (10.91) 34.53 (10.80) <0.001
    Unknown 1,078 650 428
acs_pct_unemploy_t 4.93 (4.11) 5.15 (4.23) 4.62 (3.91) <0.001
    Unknown 3,829 1,949 1,880
acs_gini_index_t 0.41 (0.06) 0.42 (0.06) 0.41 (0.06) <0.001
    Unknown 4,342 2,235 2,107
acs_median_hh_inc_t 64,069.54 (26,107.45) 62,473.16 (25,619.77) 66,320.24 (26,617.83) <0.001
    Unknown 6,682 3,667 3,015
acs_pct_health_inc_below137_t 20.68 (13.32) 21.20 (13.17) 19.96 (13.50) <0.001
    Unknown 3,981 2,022 1,959
acs_pct_inc50_t 5.84 (5.53) 5.95 (5.46) 5.68 (5.61) <0.001
    Unknown 3,981 2,022 1,959
acs_pct_hh_food_stmp_t 11.36 (10.41) 11.79 (10.45) 10.74 (10.33) <0.001
    Unknown 4,029 2,049 1,980
acs_pct_bachelor_dgr_t 18.12 (9.80) 17.50 (9.51) 18.99 (10.14) <0.001
    Unknown 1,102 664 438
acs_pct_owner_hu_t 65.81 (20.78) 66.44 (20.44) 64.92 (21.23) <0.001
    Unknown 4,029 2,049 1,980
acs_pct_vacant_hu_t 10.02 (8.57) 10.95 (8.89) 8.70 (7.92) <0.001
    Unknown 4,029 2,049 1,980
acs_pct_hu_no_veh_t 5.93 (7.21) 6.06 (7.24) 5.74 (7.16) <0.001
    Unknown 4,029 2,049 1,980
acs_pct_medicaid_any_below64_t 17.63 (12.94) 18.31 (12.79) 16.68 (13.09) <0.001
    Unknown 3,649 1,878 1,771
acs_pct_uninsured_below64_t 12.26 (9.34) 12.53 (9.29) 11.88 (9.38) <0.001
    Unknown 3,649 1,878 1,771
1 Mean (SD)
2 Welch Two Sample t-test
Table 2C: Missing Race ACS County Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Race p-value2
No, n = 412,6801 Yes, n = 293,1201
acs_avg_hh_size_c 2.59 (0.29) 2.59 (0.27) 2.60 (0.31) <0.001
acs_pct_child_disab_c 4.55 (1.42) 4.70 (1.52) 4.34 (1.22) <0.001
acs_pct_ctz_us_born_c 89.00 (8.47) 89.86 (8.23) 87.80 (8.64) <0.001
acs_pct_ctz_nonus_born_c 5.32 (4.21) 4.98 (4.21) 5.79 (4.17) <0.001
acs_pct_foreign_born_c 11.00 (8.47) 10.14 (8.23) 12.20 (8.64) <0.001
acs_pct_non_citizen_c 5.68 (4.78) 5.16 (4.52) 6.41 (5.02) <0.001
acs_pct_ctz_naturalized_c 4.51 (3.98) 4.16 (3.96) 5.00 (3.95) <0.001
acs_pct_api_lang_c 2.07 (2.16) 1.84 (2.10) 2.39 (2.21) <0.001
acs_pct_english_c 81.23 (17.80) 82.63 (17.19) 79.26 (18.46) <0.001
acs_pct_spanish_c 13.36 (16.95) 12.44 (16.22) 14.66 (17.86) <0.001
acs_pct_child_1fam_c 29.35 (7.61) 29.70 (8.06) 28.86 (6.89) <0.001
acs_pct_children_grandparent_c 7.74 (3.28) 8.05 (3.36) 7.29 (3.12) <0.001
acs_pct_hh_kid_1prnt_c 16.55 (3.88) 16.57 (3.86) 16.53 (3.91) <0.001
acs_pct_hh_no_internet_c 13.14 (6.27) 13.81 (6.54) 12.19 (5.75) <0.001
acs_pct_unemploy_c 4.90 (1.63) 5.01 (1.63) 4.75 (1.62) <0.001
acs_pct_not_labor_c 36.52 (6.81) 37.53 (6.87) 35.09 (6.46) <0.001
acs_gini_index_c 0.45 (0.03) 0.45 (0.03) 0.45 (0.03) 0.004
acs_median_hh_inc_c 60,191.18 (11,660.17) 59,702.02 (12,422.70) 60,879.87 (10,454.41) <0.001
    Unknown 4 2 2
acs_pct_health_inc_below137_c 20.62 (6.00) 20.81 (6.19) 20.37 (5.71) <0.001
acs_pct_inc50_c 5.95 (2.03) 5.94 (2.13) 5.95 (1.89) 0.004
acs_pct_hh_food_stmp_c 10.89 (4.85) 11.05 (4.90) 10.66 (4.77) <0.001
acs_pct_bachelor_dgr_c 18.69 (5.83) 18.30 (5.84) 19.24 (5.78) <0.001
acs_pct_owner_hu_c 65.29 (8.14) 66.46 (8.08) 63.65 (7.94) <0.001
acs_pct_vacant_hu_c 10.80 (6.56) 11.68 (6.75) 9.58 (6.06) <0.001
acs_pct_hu_no_veh_c 5.93 (3.35) 5.93 (3.23) 5.92 (3.52) 0.073
acs_pct_medicaid_any_below64_c 17.40 (7.25) 17.82 (7.11) 16.81 (7.40) <0.001
acs_pct_uninsured_below64_c 12.29 (6.56) 12.41 (6.59) 12.10 (6.53) <0.001
1 Mean (SD)
2 Welch Two Sample t-test
Table 2D: Missing Race SVI County Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Race p-value2
No, n = 412,6801 Yes, n = 293,1201
rpl_theme1_c 0.52 (0.26) 0.53 (0.26) 0.51 (0.27) <0.001
rpl_theme2_c 0.53 (0.28) 0.55 (0.27) 0.51 (0.28) <0.001
rpl_theme3_c 0.65 (0.22) 0.65 (0.22) 0.66 (0.21) <0.001
rpl_theme4_c 0.62 (0.22) 0.61 (0.23) 0.64 (0.19) <0.001
rpl_themes_c 0.59 (0.25) 0.59 (0.25) 0.58 (0.24) <0.001
area_sqmi_c 1,243.95 (1,477.66) 1,178.70 (1,345.49) 1,335.81 (1,641.46) <0.001
rpl_theme1_t 0.50 (0.29) 0.52 (0.28) 0.49 (0.30) <0.001
    Unknown 3,868 1,976 1,892
rpl_theme2_t 0.54 (0.28) 0.55 (0.28) 0.52 (0.28) <0.001
    Unknown 3,645 1,874 1,771
rpl_theme3_t 0.46 (0.28) 0.46 (0.28) 0.46 (0.28) <0.001
    Unknown 1,078 650 428
rpl_theme4_t 0.51 (0.28) 0.52 (0.28) 0.50 (0.28) <0.001
    Unknown 4,029 2,049 1,980
rpl_themes_t 0.52 (0.29) 0.53 (0.28) 0.50 (0.30) <0.001
    Unknown 4,228 2,138 2,090
area_sqmi_t 56.20 (252.12) 61.77 (253.72) 48.35 (249.64) <0.001
1 Mean (SD)
2 Welch Two Sample t-test
Table 2E: Missing Race COI Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Missing Race p-value2
No, n = 412,6801 Yes, n = 293,1201
r_ED_nat_t 47.40 (25.39) 45.97 (24.30) 49.32 (26.67) <0.001
    Unknown 185,374 113,601 71,773
r_HE_nat_t 44.33 (27.43) 41.78 (26.88) 47.77 (27.78) <0.001
    Unknown 185,369 113,598 71,771
r_SE_nat_t 42.73 (25.32) 40.86 (24.53) 45.26 (26.13) <0.001
    Unknown 185,544 113,657 71,887
r_COI_nat_t 43.76 (25.68) 41.79 (24.74) 46.43 (26.66) <0.001
    Unknown 185,372 113,599 71,773
1 Mean (SD)
2 Wilcoxon rank sum test
Table 2F: Missing Race for Percent Race, Ethnicity, Gender Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Missing Race p-value2
No, n = 412,6801 Yes, n = 293,1201
percent_female_t 50.37 (5.18) 50.46 (5.17) 50.23 (5.20) <0.001
    Unknown 1,078 650 428
percent_hispanic_t 19.75 (25.43) 18.59 (24.39) 21.40 (26.73) <0.001
    Unknown 1,078 650 428
percent_white_t 81.13 (17.89) 80.32 (18.88) 82.28 (16.31) <0.001
    Unknown 1,125 651 474
percent_black_t 8.82 (15.71) 10.00 (17.11) 7.16 (13.34) <0.001
    Unknown 1,125 651 474
percent_aian_t 1.13 (3.43) 1.19 (3.54) 1.05 (3.25) <0.001
    Unknown 1,125 651 474
percent_asian_t 3.28 (6.32) 3.01 (6.25) 3.66 (6.39) <0.001
    Unknown 1,125 651 474
percent_nhopi_t 0.16 (0.80) 0.14 (0.74) 0.17 (0.87) <0.001
    Unknown 1,125 651 474
percent_multi_t 5.48 (5.39) 5.34 (5.28) 5.67 (5.53) <0.001
    Unknown 1,125 651 474
percent_female_c 50.29 (1.48) 50.39 (1.59) 50.14 (1.30) <0.001
percent_hispanic_c 18.30 (20.16) 17.13 (19.29) 19.96 (21.20) <0.001
percent_white_c 81.38 (11.66) 80.90 (12.30) 82.07 (10.68) <0.001
percent_black_c 8.76 (10.64) 9.75 (11.70) 7.37 (8.74) <0.001
percent_aian_c 1.14 (2.96) 1.18 (3.06) 1.09 (2.80) <0.001
percent_asian_c 3.23 (3.64) 2.89 (3.47) 3.72 (3.80) <0.001
percent_nhopi_c 0.15 (0.40) 0.14 (0.35) 0.16 (0.45) <0.001
percent_multi_c 5.33 (2.89) 5.16 (2.87) 5.58 (2.90) <0.001
1 Mean (SD)
2 Welch Two Sample t-test

Descriptive Tables for Missing Ethnicity by Patient

Table 3A: ABFM Missing Hispanic Descriptive Statistics Using Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Ethnicity p-value2
No, n = 431,8401 Yes, n = 273,9601
Screen Test 216,753 (31%) 132,007 (31%) 84,746 (31%) 0.001
Gender


<0.001
    Female 340,417 (48%) 209,930 (49%) 130,487 (48%)
    Male 364,751 (52%) 221,823 (51%) 142,928 (52%)
    Unknown 632 87 545
race


<0.001
    AIAN 18,015 (4.4%) 17,252 (5.1%) 763 (1.0%)
    Asian 11,412 (2.8%) 7,747 (2.3%) 3,665 (4.8%)
    Black 50,872 (12%) 40,685 (12%) 10,187 (13%)
    Multiple 3,469 (0.8%) 2,583 (0.8%) 886 (1.2%)
    NHOPI 1,382 (0.3%) 1,043 (0.3%) 339 (0.4%)
    White 327,530 (79%) 266,593 (79%) 60,937 (79%)
    Unknown 293,120 95,937 197,183
1 n (%)
2 Pearson’s Chi-squared test
Table 3B: Missing Ethnicity ACS Census Tract Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Ethnicity p-value2
No, n = 431,8401 Yes, n = 273,9601
acs_avg_hh_size_t 2.68 (0.54) 2.72 (0.55) 2.61 (0.51) <0.001
    Unknown 4,399 2,176 2,223
acs_pct_child_disab_t 4.58 (4.54) 4.70 (4.53) 4.40 (4.56) <0.001
    Unknown 4,681 2,390 2,291
acs_pct_ctz_naturalized_t 4.67 (5.76) 4.92 (6.19) 4.29 (4.99) <0.001
    Unknown 1,078 651 427
acs_pct_ctz_nonus_born_t 5.47 (6.13) 5.75 (6.57) 5.05 (5.34) <0.001
    Unknown 1,078 651 427
acs_pct_ctz_us_born_t 88.66 (12.14) 87.77 (12.87) 90.06 (10.74) <0.001
    Unknown 1,078 651 427
acs_pct_foreign_born_t 11.34 (12.14) 12.23 (12.87) 9.94 (10.74) <0.001
    Unknown 1,078 651 427
acs_pct_non_citizen_t 5.87 (7.73) 6.49 (8.19) 4.89 (6.83) <0.001
    Unknown 1,078 651 427
acs_pct_api_lang_t 2.05 (4.05) 1.99 (4.29) 2.15 (3.64) <0.001
    Unknown 1,078 651 427
acs_pct_english_t 79.99 (23.18) 78.03 (24.28) 83.07 (20.97) <0.001
    Unknown 1,078 651 427
acs_pct_spanish_t 14.84 (21.95) 17.06 (22.96) 11.34 (19.74) <0.001
    Unknown 1,078 651 427
acs_pct_hh_no_internet_t 13.66 (10.16) 14.54 (10.17) 12.29 (9.99) <0.001
    Unknown 4,029 1,899 2,130
acs_pct_child_1fam_t 29.67 (19.23) 30.66 (19.03) 28.10 (19.45) <0.001
    Unknown 5,419 2,706 2,713
acs_pct_children_grandparent_t 7.95 (8.27) 8.38 (8.38) 7.27 (8.03) <0.001
    Unknown 3,892 2,053 1,839
acs_pct_hh_kid_1prnt_t 16.96 (9.38) 17.66 (9.36) 15.87 (9.30) <0.001
    Unknown 4,029 1,899 2,130
acs_pct_not_labor_t 36.03 (10.94) 36.61 (10.67) 35.11 (11.28) <0.001
    Unknown 1,078 651 427
acs_pct_unemploy_t 4.93 (4.11) 5.15 (4.20) 4.58 (3.94) <0.001
    Unknown 3,829 1,776 2,053
acs_gini_index_t 0.41 (0.06) 0.42 (0.06) 0.41 (0.06) <0.001
    Unknown 4,342 2,154 2,188
acs_median_hh_inc_t 64,069.54 (26,107.45) 62,579.93 (24,743.05) 66,421.02 (27,965.92) <0.001
    Unknown 6,682 3,846 2,836
acs_pct_health_inc_below137_t 20.68 (13.32) 21.23 (12.97) 19.82 (13.82) <0.001
    Unknown 3,981 1,878 2,103
acs_pct_inc50_t 5.84 (5.53) 5.85 (5.34) 5.83 (5.81) 0.2
    Unknown 3,981 1,878 2,103
acs_pct_hh_food_stmp_t 11.36 (10.41) 11.79 (10.30) 10.68 (10.56) <0.001
    Unknown 4,029 1,899 2,130
acs_pct_bachelor_dgr_t 18.12 (9.80) 17.01 (9.35) 19.87 (10.23) <0.001
    Unknown 1,102 663 439
acs_pct_owner_hu_t 65.81 (20.78) 65.70 (20.16) 65.99 (21.72) <0.001
    Unknown 4,029 1,899 2,130
acs_pct_vacant_hu_t 10.02 (8.57) 10.54 (8.60) 9.18 (8.46) <0.001
    Unknown 4,029 1,899 2,130
acs_pct_hu_no_veh_t 5.93 (7.21) 5.93 (6.91) 5.92 (7.66) 0.6
    Unknown 4,029 1,899 2,130
acs_pct_medicaid_any_below64_t 17.63 (12.94) 18.46 (12.74) 16.32 (13.15) <0.001
    Unknown 3,649 1,667 1,982
acs_pct_uninsured_below64_t 12.26 (9.34) 12.95 (9.35) 11.16 (9.20) <0.001
    Unknown 3,649 1,667 1,982
1 Mean (SD)
2 Welch Two Sample t-test
Table 3C: Missing Ethnicity ACS County Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Ethnicity p-value2
No, n = 431,8401 Yes, n = 273,9601
acs_avg_hh_size_c 2.59 (0.29) 2.62 (0.29) 2.55 (0.28) <0.001
acs_pct_child_disab_c 4.55 (1.42) 4.64 (1.44) 4.41 (1.37) <0.001
acs_pct_ctz_us_born_c 89.00 (8.47) 88.31 (9.00) 90.09 (7.41) <0.001
acs_pct_ctz_nonus_born_c 5.32 (4.21) 5.54 (4.55) 4.97 (3.59) <0.001
acs_pct_foreign_born_c 11.00 (8.47) 11.69 (9.00) 9.91 (7.41) <0.001
acs_pct_non_citizen_c 5.68 (4.78) 6.15 (5.04) 4.93 (4.23) <0.001
acs_pct_ctz_naturalized_c 4.51 (3.98) 4.71 (4.30) 4.19 (3.38) <0.001
acs_pct_api_lang_c 2.07 (2.16) 1.97 (2.30) 2.24 (1.91) <0.001
acs_pct_english_c 81.23 (17.80) 79.68 (18.62) 83.68 (16.14) <0.001
acs_pct_spanish_c 13.36 (16.95) 15.23 (17.60) 10.42 (15.44) <0.001
acs_pct_child_1fam_c 29.35 (7.61) 30.37 (7.97) 27.74 (6.68) <0.001
acs_pct_children_grandparent_c 7.74 (3.28) 8.06 (3.20) 7.22 (3.34) <0.001
acs_pct_hh_kid_1prnt_c 16.55 (3.88) 17.02 (3.92) 15.81 (3.70) <0.001
acs_pct_hh_no_internet_c 13.14 (6.27) 13.77 (6.33) 12.14 (6.04) <0.001
acs_pct_unemploy_c 4.90 (1.63) 5.04 (1.61) 4.69 (1.65) <0.001
acs_pct_not_labor_c 36.52 (6.81) 37.22 (6.74) 35.41 (6.77) <0.001
acs_gini_index_c 0.45 (0.03) 0.46 (0.03) 0.45 (0.03) <0.001
acs_median_hh_inc_c 60,191.18 (11,660.17) 59,876.60 (11,895.79) 60,687.05 (11,260.99) <0.001
    Unknown 4 4 0
acs_pct_health_inc_below137_c 20.62 (6.00) 20.98 (6.18) 20.07 (5.65) <0.001
acs_pct_inc50_c 5.95 (2.03) 5.93 (2.13) 5.96 (1.86) <0.001
acs_pct_hh_food_stmp_c 10.89 (4.85) 11.14 (4.97) 10.49 (4.63) <0.001
acs_pct_bachelor_dgr_c 18.69 (5.83) 17.90 (5.68) 19.95 (5.85) <0.001
acs_pct_owner_hu_c 65.29 (8.14) 65.53 (8.18) 64.92 (8.06) <0.001
acs_pct_vacant_hu_c 10.80 (6.56) 11.38 (6.52) 9.90 (6.50) <0.001
acs_pct_hu_no_veh_c 5.93 (3.35) 5.90 (3.20) 5.96 (3.58) <0.001
acs_pct_medicaid_any_below64_c 17.40 (7.25) 18.12 (7.21) 16.26 (7.16) <0.001
acs_pct_uninsured_below64_c 12.29 (6.56) 12.83 (6.62) 11.43 (6.38) <0.001
1 Mean (SD)
2 Welch Two Sample t-test
Table 3D: Missing Ethnicity SVI County Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Ethnicity p-value2
No, n = 431,8401 Yes, n = 273,9601
rpl_theme1_c 0.52 (0.26) 0.56 (0.26) 0.47 (0.27) <0.001
rpl_theme2_c 0.53 (0.28) 0.58 (0.27) 0.46 (0.27) <0.001
rpl_theme3_c 0.65 (0.22) 0.68 (0.22) 0.61 (0.21) <0.001
rpl_theme4_c 0.62 (0.22) 0.63 (0.23) 0.62 (0.20) <0.001
rpl_themes_c 0.59 (0.25) 0.62 (0.25) 0.53 (0.24) <0.001
area_sqmi_c 1,243.95 (1,477.66) 1,268.59 (1,428.46) 1,205.11 (1,551.26) <0.001
rpl_theme1_t 0.50 (0.29) 0.53 (0.28) 0.46 (0.30) <0.001
    Unknown 3,868 1,799 2,069
rpl_theme2_t 0.54 (0.28) 0.57 (0.28) 0.49 (0.28) <0.001
    Unknown 3,645 1,663 1,982
rpl_theme3_t 0.46 (0.28) 0.49 (0.28) 0.41 (0.26) <0.001
    Unknown 1,078 651 427
rpl_theme4_t 0.51 (0.28) 0.53 (0.27) 0.49 (0.28) <0.001
    Unknown 4,029 1,899 2,130
rpl_themes_t 0.52 (0.29) 0.55 (0.28) 0.47 (0.30) <0.001
    Unknown 4,228 2,023 2,205
area_sqmi_t 56.20 (252.12) 60.34 (253.38) 49.66 (249.97) <0.001
1 Mean (SD)
2 Welch Two Sample t-test
Table 3E: Missing Ethnicity COI County Descriptive Statistics by Multiple Records per Patient
Characteristic Overall, N = 705,8001 Missing Ethnicity p-value2
No, n = 431,8401 Yes, n = 273,9601
r_ED_nat_t 45 (27, 68) 42 (25, 61) 53 (33, 75) <0.001
    Unknown 185,374 112,542 72,832
r_HE_nat_t 41 (21, 68) 35 (19, 62) 55 (27, 75) <0.001
    Unknown 185,369 112,541 72,828
r_SE_nat_t 41 (21, 60) 37 (19, 58) 47 (24, 70) <0.001
    Unknown 185,544 112,641 72,903
r_COI_nat_t 41 (22, 63) 38 (20, 59) 48 (26, 71) <0.001
    Unknown 185,372 112,542 72,830
1 Median (IQR)
2 Wilcoxon rank sum test
Table 3F: Percent Missing Ethnicity by Race, Ethnicity, Gender Descriptive Statistics Using Multiple Records Per Person
Characteristic Overall, N = 705,8001 Missing Ethnicity p-value2
No, n = 431,8401 Yes, n = 273,9601
percent_female_t 50.37 (5.18) 50.35 (5.08) 50.40 (5.34) <0.001
    Unknown 1,078 651 427
percent_hispanic_t 19.75 (25.43) 22.53 (26.71) 15.38 (22.57) <0.001
    Unknown 1,078 651 427
percent_white_t 81.13 (17.89) 80.29 (18.76) 82.46 (16.32) <0.001
    Unknown 1,125 692 433
percent_black_t 8.82 (15.71) 9.49 (16.64) 7.77 (14.07) <0.001
    Unknown 1,125 692 433
percent_aian_t 1.13 (3.43) 1.14 (3.30) 1.12 (3.61) 0.10
    Unknown 1,125 692 433
percent_asian_t 3.28 (6.32) 3.24 (6.74) 3.34 (5.59) <0.001
    Unknown 1,125 692 433
percent_nhopi_t 0.16 (0.80) 0.18 (0.82) 0.12 (0.77) <0.001
    Unknown 1,125 692 433
percent_multi_t 5.48 (5.39) 5.66 (5.59) 5.19 (5.05) <0.001
    Unknown 1,125 692 433
percent_female_c 50.29 (1.48) 50.27 (1.63) 50.32 (1.22) <0.001
percent_hispanic_c 18.30 (20.16) 20.67 (20.98) 14.57 (18.16) <0.001
percent_white_c 81.38 (11.66) 80.85 (12.04) 82.23 (10.99) <0.001
percent_black_c 8.76 (10.64) 9.28 (11.05) 7.95 (9.90) <0.001
percent_aian_c 1.14 (2.96) 1.13 (2.79) 1.16 (3.20) <0.001
percent_asian_c 3.23 (3.64) 3.14 (3.92) 3.38 (3.14) <0.001
percent_nhopi_c 0.15 (0.40) 0.17 (0.35) 0.11 (0.45) <0.001
percent_multi_c 5.33 (2.89) 5.43 (2.98) 5.17 (2.73) <0.001
1 Mean (SD)
2 Welch Two Sample t-test 
293120 observations missing `race` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `race` column before passing to `tbl_summary()`.
Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient
Characteristic Overall, N = 412,6801 Race Category p-value2
AIAN, N = 18,0151 Asian, N = 11,4121 Black, N = 50,8721 Multiple, N = 3,4691 NHOPI, N = 1,3821 White, N = 327,5301
Screen Test






<0.001
    No 287,002 (70%) 17,111 (95%) 8,159 (71%) 34,838 (68%) 1,583 (46%) 1,044 (76%) 224,267 (68%)
    Yes 125,678 (30%) 904 (5.0%) 3,253 (29%) 16,034 (32%) 1,886 (54%) 338 (24%) 103,263 (32%)
Gender






<0.001
    Female 199,493 (48%) 8,822 (49%) 5,438 (48%) 24,259 (48%) 1,827 (53%) 596 (43%) 158,551 (48%)
    Male 212,991 (52%) 9,192 (51%) 5,974 (52%) 26,598 (52%) 1,642 (47%) 786 (57%) 168,799 (52%)
    Unknown 196 1 0 15 0 0 180
hispanic






<0.001
    No 266,803 (79%) 16,164 (94%) 6,793 (88%) 37,933 (93%) 2,211 (86%) 645 (62%) 203,057 (76%)
    Yes 69,100 (21%) 1,088 (6.3%) 954 (12%) 2,752 (6.8%) 372 (14%) 398 (38%) 63,536 (24%)
    Unknown 76,777 763 3,665 10,187 886 339 60,937
1 n (%)
2 Pearson’s Chi-squared test 
273960 observations missing `hispanic` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `hispanic` column before passing to `tbl_summary()`.
Table 5A: ABFM Missing Hispanic Descriptive Statistics Using Multiple Records per Patient
Characteristic Overall, N = 431,8401 Hispanic p-value2
No, N = 297,7901 Yes, N = 134,0501
Screen Test


<0.001
    No 299,833 (69%) 216,416 (73%) 83,417 (62%)
    Yes 132,007 (31%) 81,374 (27%) 50,633 (38%)
Gender


0.014
    Female 209,930 (49%) 144,408 (48%) 65,522 (49%)
    Male 221,823 (51%) 153,359 (52%) 68,464 (51%)
    Unknown 87 23 64
race


<0.001
    AIAN 17,252 (5.1%) 16,164 (6.1%) 1,088 (1.6%)
    Asian 7,747 (2.3%) 6,793 (2.5%) 954 (1.4%)
    Black 40,685 (12%) 37,933 (14%) 2,752 (4.0%)
    Multiple 2,583 (0.8%) 2,211 (0.8%) 372 (0.5%)
    NHOPI 1,043 (0.3%) 645 (0.2%) 398 (0.6%)
    White 266,593 (79%) 203,057 (76%) 63,536 (92%)
    Unknown 95,937 30,987 64,950
1 n (%)
2 Pearson’s Chi-squared test 
df_all3 <- df_all2 %>% 
     select(st_abbr_t, Screen, racenew, hispnew) 

table6a_s_abfm <- df_all3 %>% select(st_abbr_t) %>% 
  tbl_summary(
    by = NULL,
    percent = NULL,
    statistic = list(
      all_continuous() ~ "{mean} ({sd})",
      all_categorical() ~ "{n}")) %>%
  #add_overall() %>%
  #modify_spanning_header(c("stat_1") ~ "**Overall**") %>%
  #modify_header(stat_1 = "**No**, n = 412,680", stat_2 = "**Yes**, n = 293,120") %>%
  bold_labels() %>%
  modify_caption(caption = "**Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient**")
table6a_s_abfm
Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient
Characteristic N = 705,8001
st_abbr_t
    AK 103
    AL 15,441
    AR 53,656
    AZ 5,553
    CA 53,205
    CO 16,194
    CT 623
    DC 145
    DE 2,685
    FL 35,420
    GA 6,052
    HI 550
    IA 4,427
    ID 807
    IL 19,394
    IN 15,271
    KS 22,553
    KY 4,641
    LA 6,786
    MA 7,483
    MD 2,166
    ME 263
    MI 4,769
    MN 911
    MO 5,660
    MS 1,921
    MT 8,423
    NC 19,831
    ND 14
    NE 211,706
    NH 739
    NJ 4,806
    NM 5,245
    NV 489
    NY 2,344
    OH 20,062
    OK 26,367
    OR 2,808
    PA 2,027
    RI 16
    SC 10,415
    SD 80
    TN 3,805
    TX 86,337
    UT 393
    VA 7,237
    VT 4
    WA 2,145
    WI 1,215
    WV 486
    WY 2,127
1 n 
table6b_s_abfm <- df_all3 %>% select(st_abbr_t, Screen) %>% 
  tbl_summary(
    by = Screen, 
    percent = "row",
    #type = list(Screen ~ "categorical", hispanic ~ "categorical"),
    statistic = list(
      all_continuous() ~ "{mean} ({sd})",
      all_categorical() ~ "{n} ({p}%)"
    ),
    digits = list(all_categorical() ~ c(0, 1), all_continuous() ~ 2)
    ) %>%
  #add_overall() %>%
  modify_spanning_header(c("stat_1", "stat_2") ~ "**Screen**") %>%
  #modify_header(stat_1 = "**No**, n = 412,680", stat_2 = "**Yes**, n = 293,120") %>%
  bold_labels() %>%
  modify_caption(caption = "**Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient**")
table6b_s_abfm
Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient
Characteristic Screen
No, N = 489,0471 Yes, N = 216,7531
st_abbr_t

    AK 103 (100.0%) 0 (0.0%)
    AL 10,245 (66.3%) 5,196 (33.7%)
    AR 42,219 (78.7%) 11,437 (21.3%)
    AZ 5,168 (93.1%) 385 (6.9%)
    CA 41,226 (77.5%) 11,979 (22.5%)
    CO 9,645 (59.6%) 6,549 (40.4%)
    CT 310 (49.8%) 313 (50.2%)
    DC 127 (87.6%) 18 (12.4%)
    DE 2,525 (94.0%) 160 (6.0%)
    FL 28,331 (80.0%) 7,089 (20.0%)
    GA 5,553 (91.8%) 499 (8.2%)
    HI 546 (99.3%) 4 (0.7%)
    IA 4,403 (99.5%) 24 (0.5%)
    ID 403 (49.9%) 404 (50.1%)
    IL 10,575 (54.5%) 8,819 (45.5%)
    IN 14,891 (97.5%) 380 (2.5%)
    KS 20,704 (91.8%) 1,849 (8.2%)
    KY 2,375 (51.2%) 2,266 (48.8%)
    LA 6,736 (99.3%) 50 (0.7%)
    MA 1,837 (24.5%) 5,646 (75.5%)
    MD 2,058 (95.0%) 108 (5.0%)
    ME 186 (70.7%) 77 (29.3%)
    MI 3,941 (82.6%) 828 (17.4%)
    MN 866 (95.1%) 45 (4.9%)
    MO 5,537 (97.8%) 123 (2.2%)
    MS 1,298 (67.6%) 623 (32.4%)
    MT 8,252 (98.0%) 171 (2.0%)
    NC 10,588 (53.4%) 9,243 (46.6%)
    ND 13 (92.9%) 1 (7.1%)
    NE 123,260 (58.2%) 88,446 (41.8%)
    NH 192 (26.0%) 547 (74.0%)
    NJ 3,353 (69.8%) 1,453 (30.2%)
    NM 5,104 (97.3%) 141 (2.7%)
    NV 484 (99.0%) 5 (1.0%)
    NY 2,336 (99.7%) 8 (0.3%)
    OH 18,884 (94.1%) 1,178 (5.9%)
    OK 25,232 (95.7%) 1,135 (4.3%)
    OR 1,387 (49.4%) 1,421 (50.6%)
    PA 1,600 (78.9%) 427 (21.1%)
    RI 16 (100.0%) 0 (0.0%)
    SC 3,536 (34.0%) 6,879 (66.0%)
    SD 72 (90.0%) 8 (10.0%)
    TN 2,412 (63.4%) 1,393 (36.6%)
    TX 49,215 (57.0%) 37,122 (43.0%)
    UT 358 (91.1%) 35 (8.9%)
    VA 5,986 (82.7%) 1,251 (17.3%)
    VT 4 (100.0%) 0 (0.0%)
    WA 1,643 (76.6%) 502 (23.4%)
    WI 1,058 (87.1%) 157 (12.9%)
    WV 162 (33.3%) 324 (66.7%)
    WY 2,092 (98.4%) 35 (1.6%)
1 n (%) 
table6c_s_abfm <- df_all3 %>% select(st_abbr_t, racenew) %>% 
  tbl_summary(
    by = racenew, 
    percent = "row",
    #type = list(Screen ~ "categorical", hispanic ~ "categorical"),
    statistic = list(
      all_continuous() ~ "{mean} ({sd})",
      all_categorical() ~ "{n} ({p}%)"
    ),
    digits = list(all_categorical() ~ c(0, 1), all_continuous() ~ 2)
    ) %>%
  #add_overall() %>%
  modify_spanning_header(c("stat_1", "stat_2") ~ "**Race**") %>%
  modify_header(stat_1 = "**No**, n = 412,680", stat_2 = "**Yes**, n = 293,120") %>%
  bold_labels() %>%
  modify_caption(caption = "**Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient**")
table6c_s_abfm
Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient
Characteristic Race
No, n = 412,6801 Yes, n = 293,1201
st_abbr_t

    AK 12 (11.7%) 91 (88.3%)
    AL 9,618 (62.3%) 5,823 (37.7%)
    AR 44,833 (83.6%) 8,823 (16.4%)
    AZ 3,317 (59.7%) 2,236 (40.3%)
    CA 24,664 (46.4%) 28,541 (53.6%)
    CO 10,375 (64.1%) 5,819 (35.9%)
    CT 467 (75.0%) 156 (25.0%)
    DC 125 (86.2%) 20 (13.8%)
    DE 1,998 (74.4%) 687 (25.6%)
    FL 22,697 (64.1%) 12,723 (35.9%)
    GA 5,123 (84.6%) 929 (15.4%)
    HI 228 (41.5%) 322 (58.5%)
    IA 3,706 (83.7%) 721 (16.3%)
    ID 555 (68.8%) 252 (31.2%)
    IL 12,980 (66.9%) 6,414 (33.1%)
    IN 7,644 (50.1%) 7,627 (49.9%)
    KS 16,684 (74.0%) 5,869 (26.0%)
    KY 3,865 (83.3%) 776 (16.7%)
    LA 5,349 (78.8%) 1,437 (21.2%)
    MA 6,081 (81.3%) 1,402 (18.7%)
    MD 1,358 (62.7%) 808 (37.3%)
    ME 197 (74.9%) 66 (25.1%)
    MI 2,988 (62.7%) 1,781 (37.3%)
    MN 679 (74.5%) 232 (25.5%)
    MO 2,728 (48.2%) 2,932 (51.8%)
    MS 1,562 (81.3%) 359 (18.7%)
    MT 4,334 (51.5%) 4,089 (48.5%)
    NC 12,925 (65.2%) 6,906 (34.8%)
    ND 7 (50.0%) 7 (50.0%)
    NE 89,589 (42.3%) 122,117 (57.7%)
    NH 550 (74.4%) 189 (25.6%)
    NJ 1,338 (27.8%) 3,468 (72.2%)
    NM 1,462 (27.9%) 3,783 (72.1%)
    NV 309 (63.2%) 180 (36.8%)
    NY 1,338 (57.1%) 1,006 (42.9%)
    OH 11,962 (59.6%) 8,100 (40.4%)
    OK 17,266 (65.5%) 9,101 (34.5%)
    OR 1,669 (59.4%) 1,139 (40.6%)
    PA 1,628 (80.3%) 399 (19.7%)
    RI 5 (31.3%) 11 (68.8%)
    SC 8,195 (78.7%) 2,220 (21.3%)
    SD 62 (77.5%) 18 (22.5%)
    TN 2,966 (78.0%) 839 (22.0%)
    TX 58,285 (67.5%) 28,052 (32.5%)
    UT 335 (85.2%) 58 (14.8%)
    VA 4,805 (66.4%) 2,432 (33.6%)
    VT 4 (100.0%) 0 (0.0%)
    WA 1,554 (72.4%) 591 (27.6%)
    WI 1,093 (90.0%) 122 (10.0%)
    WV 436 (89.7%) 50 (10.3%)
    WY 730 (34.3%) 1,397 (65.7%)
1 n (%) 
table6d_s_abfm <- df_all3 %>% select(st_abbr_t, hispnew) %>% 
  tbl_summary(
    by = hispnew, 
    percent = "row",
    #type = list(Screen ~ "categorical", hispanic ~ "categorical"),
    statistic = list(
      all_continuous() ~ "{mean} ({sd})",
      all_categorical() ~ "{n} ({p}%)"
    ),
    digits = list(all_categorical() ~ c(0, 1), all_continuous() ~ 0)
    ) %>%
  #add_overall() %>%
  modify_spanning_header(c("stat_1", "stat_2") ~ "**Race**") %>%
  modify_header(stat_1 = "**No**, n = 412,680", stat_2 = "**Yes**, n = 293,120") %>%
  bold_labels() %>%
  modify_caption(caption = "**Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient**")

table6d_s_abfm
Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient
Characteristic Race
No, n = 412,6801 Yes, n = 293,1201
st_abbr_t

    AK 23 (22.3%) 80 (77.7%)
    AL 11,586 (75.0%) 3,855 (25.0%)
    AR 45,911 (85.6%) 7,745 (14.4%)
    AZ 3,625 (65.3%) 1,928 (34.7%)
    CA 39,181 (73.6%) 14,024 (26.4%)
    CO 8,281 (51.1%) 7,913 (48.9%)
    CT 52 (8.3%) 571 (91.7%)
    DC 104 (71.7%) 41 (28.3%)
    DE 2,105 (78.4%) 580 (21.6%)
    FL 24,048 (67.9%) 11,372 (32.1%)
    GA 4,888 (80.8%) 1,164 (19.2%)
    HI 225 (40.9%) 325 (59.1%)
    IA 770 (17.4%) 3,657 (82.6%)
    ID 536 (66.4%) 271 (33.6%)
    IL 15,051 (77.6%) 4,343 (22.4%)
    IN 9,719 (63.6%) 5,552 (36.4%)
    KS 13,991 (62.0%) 8,562 (38.0%)
    KY 3,558 (76.7%) 1,083 (23.3%)
    LA 4,833 (71.2%) 1,953 (28.8%)
    MA 2,445 (32.7%) 5,038 (67.3%)
    MD 974 (45.0%) 1,192 (55.0%)
    ME 111 (42.2%) 152 (57.8%)
    MI 1,587 (33.3%) 3,182 (66.7%)
    MN 823 (90.3%) 88 (9.7%)
    MO 2,582 (45.6%) 3,078 (54.4%)
    MS 488 (25.4%) 1,433 (74.6%)
    MT 3,322 (39.4%) 5,101 (60.6%)
    NC 11,385 (57.4%) 8,446 (42.6%)
    ND 6 (42.9%) 8 (57.1%)
    NE 106,044 (50.1%) 105,662 (49.9%)
    NH 33 (4.5%) 706 (95.5%)
    NJ 1,285 (26.7%) 3,521 (73.3%)
    NM 4,504 (85.9%) 741 (14.1%)
    NV 323 (66.1%) 166 (33.9%)
    NY 1,189 (50.7%) 1,155 (49.3%)
    OH 13,017 (64.9%) 7,045 (35.1%)
    OK 16,642 (63.1%) 9,725 (36.9%)
    OR 1,747 (62.2%) 1,061 (37.8%)
    PA 1,025 (50.6%) 1,002 (49.4%)
    RI 1 (6.3%) 15 (93.8%)
    SC 709 (6.8%) 9,706 (93.2%)
    SD 59 (73.8%) 21 (26.3%)
    TN 2,125 (55.8%) 1,680 (44.2%)
    TX 63,816 (73.9%) 22,521 (26.1%)
    UT 313 (79.6%) 80 (20.4%)
    VA 4,119 (56.9%) 3,118 (43.1%)
    VT 4 (100.0%) 0 (0.0%)
    WA 1,234 (57.5%) 911 (42.5%)
    WI 786 (64.7%) 429 (35.3%)
    WV 67 (13.8%) 419 (86.2%)
    WY 588 (27.6%) 1,539 (72.4%)
1 n (%) 
merged_table <- tbl_merge(
  tbls = list(table6a_s_abfm, table6b_s_abfm, table6c_s_abfm, table6d_s_abfm),
  tab_spanner = c("**Overall**", "**Screening**", "**Missing Race**", "**Missing Ethnicity**")
)

merged_table
Table 4A: ABFM Known Race Descriptive Statistics Using Multiple Records per Patient
Characteristic Overall Screening Missing Race Missing Ethnicity
N = 705,8001 No, N = 489,0472 Yes, N = 216,7532 No, n = 412,6802 Yes, n = 293,1202 No, n = 412,6802 Yes, n = 293,1202
st_abbr_t






    AK 103 103 (100.0%) 0 (0.0%) 12 (11.7%) 91 (88.3%) 23 (22.3%) 80 (77.7%)
    AL 15,441 10,245 (66.3%) 5,196 (33.7%) 9,618 (62.3%) 5,823 (37.7%) 11,586 (75.0%) 3,855 (25.0%)
    AR 53,656 42,219 (78.7%) 11,437 (21.3%) 44,833 (83.6%) 8,823 (16.4%) 45,911 (85.6%) 7,745 (14.4%)
    AZ 5,553 5,168 (93.1%) 385 (6.9%) 3,317 (59.7%) 2,236 (40.3%) 3,625 (65.3%) 1,928 (34.7%)
    CA 53,205 41,226 (77.5%) 11,979 (22.5%) 24,664 (46.4%) 28,541 (53.6%) 39,181 (73.6%) 14,024 (26.4%)
    CO 16,194 9,645 (59.6%) 6,549 (40.4%) 10,375 (64.1%) 5,819 (35.9%) 8,281 (51.1%) 7,913 (48.9%)
    CT 623 310 (49.8%) 313 (50.2%) 467 (75.0%) 156 (25.0%) 52 (8.3%) 571 (91.7%)
    DC 145 127 (87.6%) 18 (12.4%) 125 (86.2%) 20 (13.8%) 104 (71.7%) 41 (28.3%)
    DE 2,685 2,525 (94.0%) 160 (6.0%) 1,998 (74.4%) 687 (25.6%) 2,105 (78.4%) 580 (21.6%)
    FL 35,420 28,331 (80.0%) 7,089 (20.0%) 22,697 (64.1%) 12,723 (35.9%) 24,048 (67.9%) 11,372 (32.1%)
    GA 6,052 5,553 (91.8%) 499 (8.2%) 5,123 (84.6%) 929 (15.4%) 4,888 (80.8%) 1,164 (19.2%)
    HI 550 546 (99.3%) 4 (0.7%) 228 (41.5%) 322 (58.5%) 225 (40.9%) 325 (59.1%)
    IA 4,427 4,403 (99.5%) 24 (0.5%) 3,706 (83.7%) 721 (16.3%) 770 (17.4%) 3,657 (82.6%)
    ID 807 403 (49.9%) 404 (50.1%) 555 (68.8%) 252 (31.2%) 536 (66.4%) 271 (33.6%)
    IL 19,394 10,575 (54.5%) 8,819 (45.5%) 12,980 (66.9%) 6,414 (33.1%) 15,051 (77.6%) 4,343 (22.4%)
    IN 15,271 14,891 (97.5%) 380 (2.5%) 7,644 (50.1%) 7,627 (49.9%) 9,719 (63.6%) 5,552 (36.4%)
    KS 22,553 20,704 (91.8%) 1,849 (8.2%) 16,684 (74.0%) 5,869 (26.0%) 13,991 (62.0%) 8,562 (38.0%)
    KY 4,641 2,375 (51.2%) 2,266 (48.8%) 3,865 (83.3%) 776 (16.7%) 3,558 (76.7%) 1,083 (23.3%)
    LA 6,786 6,736 (99.3%) 50 (0.7%) 5,349 (78.8%) 1,437 (21.2%) 4,833 (71.2%) 1,953 (28.8%)
    MA 7,483 1,837 (24.5%) 5,646 (75.5%) 6,081 (81.3%) 1,402 (18.7%) 2,445 (32.7%) 5,038 (67.3%)
    MD 2,166 2,058 (95.0%) 108 (5.0%) 1,358 (62.7%) 808 (37.3%) 974 (45.0%) 1,192 (55.0%)
    ME 263 186 (70.7%) 77 (29.3%) 197 (74.9%) 66 (25.1%) 111 (42.2%) 152 (57.8%)
    MI 4,769 3,941 (82.6%) 828 (17.4%) 2,988 (62.7%) 1,781 (37.3%) 1,587 (33.3%) 3,182 (66.7%)
    MN 911 866 (95.1%) 45 (4.9%) 679 (74.5%) 232 (25.5%) 823 (90.3%) 88 (9.7%)
    MO 5,660 5,537 (97.8%) 123 (2.2%) 2,728 (48.2%) 2,932 (51.8%) 2,582 (45.6%) 3,078 (54.4%)
    MS 1,921 1,298 (67.6%) 623 (32.4%) 1,562 (81.3%) 359 (18.7%) 488 (25.4%) 1,433 (74.6%)
    MT 8,423 8,252 (98.0%) 171 (2.0%) 4,334 (51.5%) 4,089 (48.5%) 3,322 (39.4%) 5,101 (60.6%)
    NC 19,831 10,588 (53.4%) 9,243 (46.6%) 12,925 (65.2%) 6,906 (34.8%) 11,385 (57.4%) 8,446 (42.6%)
    ND 14 13 (92.9%) 1 (7.1%) 7 (50.0%) 7 (50.0%) 6 (42.9%) 8 (57.1%)
    NE 211,706 123,260 (58.2%) 88,446 (41.8%) 89,589 (42.3%) 122,117 (57.7%) 106,044 (50.1%) 105,662 (49.9%)
    NH 739 192 (26.0%) 547 (74.0%) 550 (74.4%) 189 (25.6%) 33 (4.5%) 706 (95.5%)
    NJ 4,806 3,353 (69.8%) 1,453 (30.2%) 1,338 (27.8%) 3,468 (72.2%) 1,285 (26.7%) 3,521 (73.3%)
    NM 5,245 5,104 (97.3%) 141 (2.7%) 1,462 (27.9%) 3,783 (72.1%) 4,504 (85.9%) 741 (14.1%)
    NV 489 484 (99.0%) 5 (1.0%) 309 (63.2%) 180 (36.8%) 323 (66.1%) 166 (33.9%)
    NY 2,344 2,336 (99.7%) 8 (0.3%) 1,338 (57.1%) 1,006 (42.9%) 1,189 (50.7%) 1,155 (49.3%)
    OH 20,062 18,884 (94.1%) 1,178 (5.9%) 11,962 (59.6%) 8,100 (40.4%) 13,017 (64.9%) 7,045 (35.1%)
    OK 26,367 25,232 (95.7%) 1,135 (4.3%) 17,266 (65.5%) 9,101 (34.5%) 16,642 (63.1%) 9,725 (36.9%)
    OR 2,808 1,387 (49.4%) 1,421 (50.6%) 1,669 (59.4%) 1,139 (40.6%) 1,747 (62.2%) 1,061 (37.8%)
    PA 2,027 1,600 (78.9%) 427 (21.1%) 1,628 (80.3%) 399 (19.7%) 1,025 (50.6%) 1,002 (49.4%)
    RI 16 16 (100.0%) 0 (0.0%) 5 (31.3%) 11 (68.8%) 1 (6.3%) 15 (93.8%)
    SC 10,415 3,536 (34.0%) 6,879 (66.0%) 8,195 (78.7%) 2,220 (21.3%) 709 (6.8%) 9,706 (93.2%)
    SD 80 72 (90.0%) 8 (10.0%) 62 (77.5%) 18 (22.5%) 59 (73.8%) 21 (26.3%)
    TN 3,805 2,412 (63.4%) 1,393 (36.6%) 2,966 (78.0%) 839 (22.0%) 2,125 (55.8%) 1,680 (44.2%)
    TX 86,337 49,215 (57.0%) 37,122 (43.0%) 58,285 (67.5%) 28,052 (32.5%) 63,816 (73.9%) 22,521 (26.1%)
    UT 393 358 (91.1%) 35 (8.9%) 335 (85.2%) 58 (14.8%) 313 (79.6%) 80 (20.4%)
    VA 7,237 5,986 (82.7%) 1,251 (17.3%) 4,805 (66.4%) 2,432 (33.6%) 4,119 (56.9%) 3,118 (43.1%)
    VT 4 4 (100.0%) 0 (0.0%) 4 (100.0%) 0 (0.0%) 4 (100.0%) 0 (0.0%)
    WA 2,145 1,643 (76.6%) 502 (23.4%) 1,554 (72.4%) 591 (27.6%) 1,234 (57.5%) 911 (42.5%)
    WI 1,215 1,058 (87.1%) 157 (12.9%) 1,093 (90.0%) 122 (10.0%) 786 (64.7%) 429 (35.3%)
    WV 486 162 (33.3%) 324 (66.7%) 436 (89.7%) 50 (10.3%) 67 (13.8%) 419 (86.2%)
    WY 2,127 2,092 (98.4%) 35 (1.6%) 730 (34.3%) 1,397 (65.7%) 588 (27.6%) 1,539 (72.4%)
1 n
2 n (%)