#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 | 3 | |
|---|---|---|---|
| Female; Woman; Girl | 2441 | 1925 | 498 |
| Male; Man; Boy | 2725 | 1972 | 453 |
| Nonbinary | 2 | 2 | 22 |
| Not Reported | 0 | 118 | 6 |
| Prefer Not to Respond | 0 | 1 | 4 |
Caregiver Gender
table.cgen <- table(data$caregivergender,data$phase)
kbl(table.cgen) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| Female; Woman; Girl | 3886 | 3028 | 152 |
| Male; Man; Boy | 1044 | 848 | 95 |
| Nonbinary | 0 | 12 | 83 |
| Not Reported | 238 | 128 | 652 |
| Prefer Not to Respond | 0 | 2 | 1 |
Patient Age
table.page <- table(data$childage,data$phase)
kbl(table.page) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| 13-17 years | 1327 | 908 | 298 |
| 18+ | 123 | 93 | 21 |
| 2-4 years | 796 | 662 | 142 |
| 5-12 years | 1594 | 1297 | 314 |
| less than 2 years | 1328 | 940 | 175 |
| Not Reported | 0 | 118 | 33 |
Caregiver Age
table.cage <- table(data$caregiverage,data$phase)
kbl(table.cage) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| 11 | 0 | 0 | 1 |
| 18-24 years | 248 | 176 | 39 |
| 25-34 years | 1581 | 1172 | 241 |
| 35-44 years | 2054 | 1681 | 390 |
| 45-54 years | 937 | 757 | 176 |
| 55-64 years | 148 | 99 | 33 |
| 65-74 years | 14 | 16 | 3 |
| 75+ | 1 | 2 | 1 |
| Not Reported | 185 | 115 | 99 |
Education
table.edu <- table(data$education2,data$phase)
kbl(table.edu) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| 4 year college graduate | 1154 | 964 | 183 |
| 8 grade or less | 166 | 87 | 67 |
| High School grad or GED | 815 | 642 | 209 |
| More than 4 year college Degree | 942 | 853 | 184 |
| Not Reported | 58 | 43 | 53 |
| Prefer not to answer this question | 0 | 0 | 4 |
| Some college or 2 year degree | 1765 | 1225 | 225 |
| Some High School but did not graduate | 268 | 204 | 58 |
Income
table.income <- table(data$income2,data$phase)
kbl(table.income) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| $0-$2,500 | 0 | 51 | 36 |
| $2,500-$5,000 | 0 | 24 | 23 |
| $5,000-$7,500 | 0 | 30 | 30 |
| $7,500+ | 0 | 35 | 36 |
| I don’t know | 0 | 20 | 38 |
| Not Reported | 5168 | 3845 | 793 |
| Prefer not to answer | 0 | 13 | 27 |
Language
table.lang <- table(data$langofcare,data$phase)
kbl(table.lang) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| Arabic | 0 | 29 | 27 |
| Chinese | 10 | 2 | 13 |
| English | 4812 | 3814 | 746 |
| Language not listed | 0 | 0 | 8 |
| Russian | 5 | 0 | 2 |
| Somali | 3 | 3 | 14 |
| Spanish | 331 | 162 | 163 |
| Vietnamese | 7 | 8 | 10 |
Legal
table.legal <- table(data$legal2,data$phase)
kbl(table.legal) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| No | 50 | 38 | 18 |
| Not Reported | 363 | 321 | 250 |
| Yes | 4755 | 3659 | 715 |
Caregiver Relation
table.relation <- table(data$caregivertype,data$phase)
kbl(table.relation) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| Aunt or Uncle | 8 | 8 | 4 |
| Father | 1027 | 824 | 168 |
| Grandfather | 1 | 4 | 0 |
| Grandmother | 21 | 29 | 7 |
| Mother | 3920 | 3016 | 700 |
| Not Reported | 147 | 112 | 94 |
| Older brother or sister | 5 | 2 | 3 |
| Other | 24 | 11 | 4 |
| Stepfather | 5 | 8 | 2 |
| Stepmother | 10 | 4 | 1 |
Patient Race
table.prace <- table(data$childrace,data$phase)
kbl(table.prace) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| American Indian or Alaskan native | 94 | 58 | 6 |
| Asian | 355 | 297 | 21 |
| Black or African American | 194 | 153 | 37 |
| Latino or Hispanic | 537 | 394 | 132 |
| Native Hawaiian or other Pacific Islander | 65 | 50 | 42 |
| Not Reported | 47 | 270 | 653 |
| Other or Multiracial | 1193 | 742 | 32 |
| White | 2683 | 2054 | 60 |
Caregiver Race
table.crace <- table(data$caregiverrace,data$phase)
kbl(table.crace) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| 1 | 2 | 3 | |
|---|---|---|---|
| American Indian or Alaskan native | 95 | 68 | 9 |
| Asian | 355 | 342 | 32 |
| Black or African American | 202 | 162 | 28 |
| Latino or Hispanic | 692 | 489 | 161 |
| Multiracial | 0 | 0 | 21 |
| Native Hawaiian or other Pacific Islander | 86 | 59 | 2 |
| Not Reported | 99 | 52 | 648 |
| Race not listed | 417 | 361 | 11 |
| White | 3222 | 2485 | 71 |
Phase
table.phase <- table(data$phase)
kbl(table.phase) %>%
kable_paper(bootstrap_options = "striped", full_width = F)
| Var1 | Freq |
|---|---|
| 1 | 5168 |
| 2 | 4018 |
| 3 | 983 |