#useing the clean dataset w/ labels

PASAbstractClean_labels <- read_csv("PASAbstractClean_labels.csv")
## New names:
## Rows: 10169 Columns: 18
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," chr
## (14): year, month, day, childgender, caregivergender, childrace, caregiv... dbl
## (4): ...1, record_id, project, phase
## ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## • `` -> `...1`
data<-PASAbstractClean_labels

Patient Gender

table.pgen <- table(data$childgender,data$phase)

kbl(table.pgen) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
Female; Woman; Girl 4366 498
Male; Man; Boy 4697 453
Nonbinary 4 22
Not Reported 118 6
Prefer Not to Respond 1 4

Caregiver Gender

table.cgen <- table(data$caregivergender,data$phase)

kbl(table.cgen) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
Female; Woman; Girl 6914 152
Male; Man; Boy 1892 95
Nonbinary 12 83
Not Reported 366 652
Prefer Not to Respond 2 1

Patient Age

table.page <- table(data$childage,data$phase)

kbl(table.page) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
13-17 years 2235 298
18+ 216 21
2-4 years 1458 142
5-12 years 2891 314
less than 2 years 2268 175
Not Reported 118 33

Caregiver Age

table.cage <- table(data$caregiverage,data$phase)

kbl(table.cage) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
11 0 1
18-24 years 424 39
25-34 years 2753 241
35-44 years 3735 390
45-54 years 1694 176
55-64 years 247 33
65-74 years 30 3
75+ 3 1
Not Reported 300 99

Education

table.edu <- table(data$education2,data$phase)

kbl(table.edu) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
4 year college graduate 2118 183
8 grade or less 253 67
High School grad or GED 1457 209
More than 4 year college Degree 1795 184
Not Reported 101 53
Prefer not to answer this question 0 4
Some college or 2 year degree 2990 225
Some High School but did not graduate 472 58

Income

table.income <- table(data$income2,data$phase)

kbl(table.income) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
$0-$2,500 51 36
$2,500-$5,000 24 23
$5,000-$7,500 30 30
$7,500+ 35 36
I don’t know 20 38
Not Reported 9013 793
Prefer not to answer 13 27

Language

table.lang <- table(data$langofcare,data$phase)

kbl(table.lang) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
Arabic 29 27
Chinese 12 13
English 8626 746
Language not listed 0 8
Russian 5 2
Somali 6 14
Spanish 493 163
Vietnamese 15 10

Legal

table.legal <- table(data$legal2,data$phase)

kbl(table.legal) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
No 88 18
Not Reported 684 250
Yes 8414 715

Caregiver Relation

table.relation <- table(data$caregivertype,data$phase)

kbl(table.relation) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
Aunt or Uncle 16 4
Father 1851 168
Grandfather 5 0
Grandmother 50 7
Mother 6936 700
Not Reported 259 94
Older brother or sister 7 3
Other 35 4
Stepfather 13 2
Stepmother 14 1

Patient Race

table.prace <- table(data$childrace,data$phase)

kbl(table.prace) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
American Indian or Alaskan native 152 6
Asian 652 21
Black or African American 347 37
Latino or Hispanic 931 132
Native Hawaiian or other Pacific Islander 115 42
Not Reported 317 653
Other or Multiracial 1935 32
White 4737 60

Caregiver Race

table.crace <- table(data$caregiverrace,data$phase)

kbl(table.crace) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
1 2
American Indian or Alaskan native 163 9
Asian 697 32
Black or African American 364 28
Latino or Hispanic 1181 161
Native Hawaiian or other Pacific Islander 145 2
Not Reported 151 648
Other or Multiracial 778 32
White 5707 71

Phase

table.phase <- table(data$phase)

kbl(table.phase) %>%
  kable_paper(bootstrap_options = "striped", full_width = F)
Var1 Freq
1 9186
2 983