QOL baseline analysis
Jacqueline Burgara
7/20/2021
```
Firstly we want to load in the files we will be using as well as combine the data as needed.
pedsql<- read_excel("C:/Users/burga/Downloads/PedsQL No PHI 2019.xlsx",
sheet = "Calculations ") #read pedsql data baseline sheet## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...7
## * `` -> ...11fs2r <- read_excel("C:/Users/burga/Downloads/FS2R Scoring no PHI 2019.xlsx",
sheet = "Calculations") #read fs2r data baseline sheet
demographic.en <- read_csv("C:/Users/burga/Downloads/OAPEnglish_Dem_2019.csv")##
## -- Column specification --------------------------------------------------------
## cols(
## .default = col_double(),
## gender_other = col_logical(),
## other_related = col_character(),
## guard_gender_other = col_character()
## )
## i Use `spec()` for the full column specifications.## Warning: 1 parsing failure.
## row col expected actual file
## 1039 gender_other 1/0/T/F/TRUE/FALSE X (Non-Binary) 'C:/Users/burga/Downloads/OAPEnglish_Dem_2019.csv'demographic.sp <-read_csv("C:/Users/burga/Downloads/OAPSpanish_Dem_2019.csv")##
## -- Column specification --------------------------------------------------------
## cols(
## .default = col_double(),
## gender_other = col_logical(),
## other_related = col_logical(),
## guard_gender_other = col_logical()
## )
## i Use `spec()` for the full column specifications.#select only the need columns
pedsql.clean<- pedsql[ -c(2:11,13,15) ]
fs2r.clean <- fs2r[-c(2:10,12)]#data clean up
#we didn't collect unit every time so we are going to ignore those columns
dem.clean.en <- demographic.en[ -c(2) ]
dem.clean.sp <-demographic.sp[ -c(5) ]
dem.merge <-rbind(dem.clean.en,dem.clean.sp)
# childgender
dem.merge$childgender <- as.factor(dem.merge$childgender)
levels (dem.merge$childgender) <-gsub("0","Male",levels(dem.merge$childgender))
levels (dem.merge$childgender) <-gsub("1","Female",levels(dem.merge$childgender))
levels (dem.merge$childgender) <-gsub("2","Other",levels(dem.merge$childgender))
levels (dem.merge$childgender) <-gsub("3","Prefer not to answer",levels(dem.merge$childgender))
#interviewlang
dem.merge$interviewlang <- as.factor(dem.merge$interviewlang)
levels (dem.merge$interviewlang) <-gsub("1","English",levels(dem.merge$interviewlang))
levels (dem.merge$interviewlang) <-gsub("2","Spanish",levels(dem.merge$interviewlang))
levels (dem.merge$interviewlang) <-gsub("3","Vietnamese",levels(dem.merge$interviewlang))
levels (dem.merge$interviewlang) <-gsub("4","Russian",levels(dem.merge$interviewlang))
levels (dem.merge$interviewlang) <-gsub("5","Chinese",levels(dem.merge$interviewlang))
levels (dem.merge$interviewlang) <-gsub("6","Somali",levels(dem.merge$interviewlang))
#interp_needed
dem.merge$interp_needed<- as.factor(dem.merge$interp_needed)
levels (dem.merge$interp_needed) <-gsub("0","No",levels(dem.merge$interp_needed))
levels (dem.merge$interp_needed) <-gsub("1","Yes",levels(dem.merge$interp_needed))
#pq_method
dem.merge$pq_method<- as.factor(dem.merge$pq_method)
levels (dem.merge$pq_method) <-gsub("0","Self administered",levels(dem.merge$pq_method))
levels (dem.merge$pq_method) <-gsub("1","Via telephone interview",levels(dem.merge$pq_method))
#interviewlang_change
dem.merge$interviewlang_change <- as.factor(dem.merge$interviewlang_change )
levels (dem.merge$interviewlang_change ) <-gsub("1","English",levels(dem.merge$interviewlang_change ))
levels (dem.merge$interviewlang_change ) <-gsub("2","Spanish",levels(dem.merge$interviewlang_change ))
levels (dem.merge$interviewlang_change ) <-gsub("3","Vietnamese",levels(dem.merge$interviewlang_change ))
levels (dem.merge$interviewlang_change ) <-gsub("4","Russian",levels(dem.merge$interviewlang_change ))
levels (dem.merge$interviewlang_change ) <-gsub("5","Chinese",levels(dem.merge$interviewlang_change ))
levels (dem.merge$interviewlang_change ) <-gsub("6","Somali",levels(dem.merge$interviewlang_change ))
#related
dem.merge$related<- as.factor(dem.merge$related)
levels (dem.merge$related) <-gsub("1","Mother",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("2","Father",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("3","Stepmother",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("4","Stepfather",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("5","Grandmother",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("6","Grandfather",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("8","Aunt or Uncle",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("9","Older brother or sister",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("10","Other relative",levels(dem.merge$related))
levels (dem.merge$related) <-gsub("7","Other relative",levels(dem.merge$related))
#other_related
#guard_gender
dem.merge$guard_gender<- as.factor(dem.merge$guard_gender)
levels (dem.merge$guard_gender) <-gsub("0","Male",levels(dem.merge$guard_gender))
levels (dem.merge$guard_gender) <-gsub("1","Female",levels(dem.merge$guard_gender))
levels (dem.merge$guard_gender) <-gsub("2","Other",levels(dem.merge$guard_gender))
levels (dem.merge$guard_gender) <-gsub("3","Prefer not to answer",levels(dem.merge$guard_gender))
#guard_gender_other
#parentage
#dem.merge$parentage<- as.numeric(dem.merge$parentage)
#levels (dem.merge$parentage) <-gsub("1","18-24",levels(dem.merge$parentage))
#levels (dem.merge$parentage) <-gsub("2","25-34",levels(dem.merge$parentage))
#levels (dem.merge$parentage) <-gsub("3","35-44",levels(dem.merge$parentage))
#levels (dem.merge$parentage) <-gsub("4","45-54",levels(dem.merge$parentage))
#levels (dem.merge$parentage) <-gsub("5","55-64",levels(dem.merge$parentage))
#levels (dem.merge$parentage) <-gsub("6","65-74",levels(dem.merge$parentage))
#levels (dem.merge$parentage) <-gsub("7","75+",levels(dem.merge$parentage))
dem.merge$parentage<- as.factor(dem.merge$parentage)
#education
dem.merge$education<- as.factor(dem.merge$education)
levels (dem.merge$education) <-gsub("1","8th grade or less",levels(dem.merge$education))
levels (dem.merge$education) <-gsub("2","Some high school, but did not graduate",levels(dem.merge$education))
levels (dem.merge$education) <-gsub("3","high school grad or GED",levels(dem.merge$education))
levels (dem.merge$education) <-gsub("4","Some college or 2 year degree (or trade or technical school)",levels(dem.merge$education))
levels (dem.merge$education) <-gsub("5","4-year college graduate",levels(dem.merge$education))
levels (dem.merge$education) <-gsub("6","More than 4-year college degree",levels(dem.merge$education))
#race___1 race___2 race___3 race___4 race___5 race___6 race___7
dem.merge$race___1<- as.factor(dem.merge$race___1)
levels (dem.merge$race___1) <-gsub("0","",levels(dem.merge$race___1))
levels (dem.merge$race___1) <-gsub("1","White",levels(dem.merge$race___1))
dem.merge$race___2<- as.factor(dem.merge$race___2)
levels (dem.merge$race___2) <-gsub("0","",levels(dem.merge$race___2))
levels (dem.merge$race___2) <-gsub("1","Black or African American",levels(dem.merge$race___2))
dem.merge$race___3<- as.factor(dem.merge$race___3)
levels (dem.merge$race___3) <-gsub("0","",levels(dem.merge$race___3))
levels (dem.merge$race___3) <-gsub("1","Latino or Hispanic",levels(dem.merge$race___3))
dem.merge$race___4<- as.factor(dem.merge$race___4)
levels (dem.merge$race___4) <-gsub("0","",levels(dem.merge$race___4))
levels (dem.merge$race___4) <-gsub("1","Asian",levels(dem.merge$race___4))
dem.merge$race___5<- as.factor(dem.merge$race___5)
levels (dem.merge$race___5) <-gsub("0","",levels(dem.merge$race___5))
levels (dem.merge$race___5) <-gsub("1","Native Hawaiian or other Pacific Islander",levels(dem.merge$race___5))
dem.merge$race___6<- as.factor(dem.merge$race___6)
levels (dem.merge$race___6) <-gsub("0","",levels(dem.merge$race___6))
levels (dem.merge$race___6) <-gsub("1","American Indian, or Alaskan Indian or Alaskan Native",levels(dem.merge$race___6))
dem.merge$race___7<- as.factor(dem.merge$race___7)
levels (dem.merge$race___7) <-gsub("0","",levels(dem.merge$race___7))
levels (dem.merge$race___7) <-gsub("1","Other or multiracial",levels(dem.merge$race___7))
dem.merge$race.ethnicity <- paste(dem.merge$race___1, dem.merge$race___2, dem.merge$race___3, dem.merge$race___4, dem.merge$race___5, dem.merge$race___6, dem.merge$race___7)
#childrace___1 childrace___2 childrace___3 childrace___4 childrace___5 childrace___6 childrace___7
dem.merge$childrace___1<- as.factor(dem.merge$childrace___1)
levels (dem.merge$childrace___1) <-gsub("0","",levels(dem.merge$childrace___1))
levels (dem.merge$childrace___1) <-gsub("1","White",levels(dem.merge$childrace___1))
dem.merge$childrace___2<- as.factor(dem.merge$childrace___2)
levels (dem.merge$childrace___2) <-gsub("0","",levels(dem.merge$childrace___2))
levels (dem.merge$childrace___2) <-gsub("1","Black or African American",levels(dem.merge$childrace___2))
dem.merge$childrace___3<- as.factor(dem.merge$childrace___3)
levels (dem.merge$childrace___3) <-gsub("0","",levels(dem.merge$childrace___3))
levels (dem.merge$childrace___3) <-gsub("1","Latino or Hispanic",levels(dem.merge$childrace___3))
dem.merge$childrace___4<- as.factor(dem.merge$childrace___4)
levels (dem.merge$childrace___4) <-gsub("0","",levels(dem.merge$childrace___4))
levels (dem.merge$childrace___4) <-gsub("1","Asian",levels(dem.merge$childrace___4))
dem.merge$childrace___5<- as.factor(dem.merge$childrace___5)
levels (dem.merge$childrace___5) <-gsub("0","",levels(dem.merge$childrace___5))
levels (dem.merge$childrace___5) <-gsub("1","Native Hawaiian or other Pacific Islander",levels(dem.merge$childrace___5))
dem.merge$childrace___6<- as.factor(dem.merge$childrace___6)
levels (dem.merge$childrace___6) <-gsub("0","",levels(dem.merge$childrace___6))
levels (dem.merge$childrace___6) <-gsub("1","American Indian, or Alaskan Indian or Alaskan Native",levels(dem.merge$childrace___6))
dem.merge$childrace___7<- as.factor(dem.merge$childrace___7)
levels (dem.merge$childrace___7) <-gsub("0","",levels(dem.merge$childrace___7))
levels (dem.merge$childrace___7) <-gsub("1","Other or multiracial",levels(dem.merge$childrace___7))
dem.merge$race.ethnicity.child <- paste(dem.merge$childrace___1, dem.merge$childrace___2, dem.merge$childrace___3, dem.merge$childrace___4, dem.merge$childrace___5, dem.merge$childrace___6, dem.merge$childrace___7)
dem.final <-dem.merge[ -c(4,10,12,15:28) ]Next we want to get rid of any blanks and merge our data.
#get rid of blanks
pedsql.final <- pedsql.clean %>%
mutate_all(~ifelse(. %in% c("N/A", "null", ""), NA, .)) %>%
na.omit()
fs2r.final <- fs2r.clean %>%
mutate_all(~ifelse(. %in% c("N/A", "null", ""), NA, .)) %>%
na.omit()
#join data sets
#there is a weird error going on in the joining so I just made a second pedsql.final
join1 <- rbind(pedsql.final,fs2r.final) #join the scores of both data sets
join2 <- inner_join(join1,dem.final, by= "record_id") #join the scores and demographic data
QOL.Equity.Exploraton <- select(join2,-c()) #deleate any possible doubles
qol_final <- QOL.Equity.Exploratonqol_final$`Back to Baseline` <- as.factor(qol_final$`Back to Baseline`)
levels (qol_final$`Back to Baseline`) <-gsub("0","did not return to baseline",levels(qol_final$`Back to Baseline`))
levels (qol_final$`Back to Baseline`) <-gsub("1","returned to baseline",levels(qol_final$`Back to Baseline`))
#change American Indian, or Alaskan Indian or Alaskan Native to indiginous so that graphs dont look weird when factoring in r&e
qol_final$r.e.parent <- as.factor(qol_final$race.ethnicity)
levels (qol_final$r.e.parent) <-gsub("American Indian, or Alaskan Indian or Alaskan Native","Indigenous",levels(qol_final$r.e.parent))
qol_final$r.e.child <- as.factor(qol_final$race.ethnicity.child)
levels (qol_final$r.e.child) <-gsub("American Indian, or Alaskan Indian or Alaskan Native","Indigenous",levels(qol_final$r.e.child))Our final data set is qol_final, now we just need to make the graphs and make some counts left NAs as they mean something here
#parent education and parent/child race and ethnicity
ggplot(qol_final)+
geom_jitter(aes(x=r.e.child, y=education,color=`Back to Baseline`))+
labs(x = "Child race and ethnicity", y= "Parent education", title = 'Parent Education and Child Race & Ethnicity effects on baseline',
caption = "")+
theme_classic()
ggplot(qol_final)+
geom_jitter(aes( x=r.e.parent, y=education,color=`Back to Baseline`))+
labs(x = "Parent race and ethnicity", y= "Parent education", title = 'Parent Education and Race & Ethicity effects on baseline',
caption = "")+
theme_classic()
table_1<-qol_final %>% count(education,r.e.parent,`Back to Baseline`, sort = TRUE)
#parent race and child race
ggplot(qol_final)+
geom_jitter(aes(x=r.e.child, y=r.e.parent,color=`Back to Baseline`))+
labs(x = "Child race and ethnicity", y= "Parent race and ethnicity", title = 'Parent and Child Race and Ethnicity effects on baseline',
caption = "")+
theme_classic()
table_2<-qol_final %>% count(r.e.child,r.e.parent,`Back to Baseline`, sort = TRUE)
#View(table_2)
#child gender and race
ggplot(qol_final)+
geom_jitter(aes(x=r.e.child, y=childgender, color=`Back to Baseline`))+
labs(x = "Child race and ethnicity", y= "Child Gender", title = 'Child Race and Ethnicity and Gender effects on baseline',
caption = "")+
theme_classic()
table_3<-qol_final %>% count(r.e.child,childgender,`Back to Baseline`, sort = TRUE)
#baseline and language
ggplot(qol_final)+
geom_jitter(aes(x=interp_needed, y=interviewlang_change,color=`Back to Baseline`))+
labs(x = "Interpretor needed", y= "Survey Language", title = 'Interpretor need and language effects on baseline',
caption = "")+
theme_classic()
table_4<-qol_final %>% count(interp_needed,interviewlang_change,`Back to Baseline`, sort = TRUE)Tables
- Organized by race/ethnicity, education, language
tinytex::reinstall_tinytex()## If reinstallation fails, try install_tinytex() again. Then install the following packages:
##
## tinytex::tlmgr_install(c("amscls", "amsfonts", "amsmath", "atbegshi", "atveryend", "auxhook", "babel", "bibtex", "bigintcalc", "bitset", "booktabs", "cm", "dehyph", "dvipdfmx", "dvips", "ec", "epstopdf-pkg", "etex", "etexcmds", "etoolbox", "euenc", "everyshi", "fancyvrb", "filehook", "firstaid", "float", "fontspec", "framed", "geometry", "gettitlestring", "glyphlist", "graphics", "graphics-cfg", "graphics-def", "grffile", "helvetic", "hycolor", "hyperref", "hyph-utf8", "hyphen-base", "iftex", "inconsolata", "infwarerr", "intcalc", "knuth-lib", "kpathsea", "kvdefinekeys", "kvoptions", "kvsetkeys", "l3backend", "l3kernel", "l3packages", "latex", "latex-amsmath-dev", "latex-bin", "latex-fonts", "latex-tools-dev", "latexconfig", "latexmk", "letltxmacro", "lm", "lm-math", "ltxcmds", "lua-alt-getopt", "luahbtex", "lualatex-math", "lualibs", "luaotfload", "luatex", "mdwtools", "metafont", "mfware", "modes", "natbib", "pdfescape", "pdftex", "pdftexcmds", "plain", "psnfss", "refcount", "rerunfilecheck", "scheme-infraonly", "stringenc", "symbol", "tex", "tex-ini-files", "texlive-scripts", "texlive.infra", "times", "tipa", "tlgs", "tlperl", "tools", "unicode-data", "unicode-math", "uniquecounter", "url", "xcolor", "xetex", "xetexconfig", "xkeyval", "xunicode", "zapfding"))## The directory C:\Users\burga\AppData\Roaming\TinyTeX/texmf-local is not empty. It will be backed up to C:\Users\burga\AppData\Local\Temp\Rtmp8gCz3T\file12e8494e23c0 and restored later.kable(table_1,booktabs = T, col.names = c("Parent Education","Parent Race & Ethnicity","Baseline Status", "n"), caption = " Table 1: Baseline Staus based on Parent education and race/ethnicity")%>%
kableExtra::kable_styling(latex_options = c("striped","scale_down"))| Parent Education | Parent Race & Ethnicity | Baseline Status | n |
|---|---|---|---|
| Some college or 2 year degree (or trade or technical school) | White | returned to baseline | 171 |
| 4-year college graduate | White | returned to baseline | 160 |
| More than 4-year college degree | White | returned to baseline | 120 |
| 4-year college graduate | White | did not return to baseline | 102 |
| More than 4-year college degree | White | did not return to baseline | 94 |
| Some college or 2 year degree (or trade or technical school) | White | did not return to baseline | 88 |
| high school grad or GED | White | did not return to baseline | 51 |
| high school grad or GED | White | returned to baseline | 51 |
| Some college or 2 year degree (or trade or technical school) | Latino or Hispanic | returned to baseline | 31 |
| high school grad or GED | Latino or Hispanic | returned to baseline | 29 |
| 4-year college graduate | Asian | returned to baseline | 27 |
| Some high school, but did not graduate | Latino or Hispanic | returned to baseline | 25 |
| More than 4-year college degree | Asian | did not return to baseline | 22 |
| Some college or 2 year degree (or trade or technical school) | Black or African American | returned to baseline | 21 |
| 4-year college graduate | Asian | did not return to baseline | 19 |
| 8th grade or less | Latino or Hispanic | returned to baseline | 17 |
| More than 4-year college degree | Asian | returned to baseline | 16 |
| Some college or 2 year degree (or trade or technical school) | Other or multiracial | returned to baseline | 11 |
| Some college or 2 year degree (or trade or technical school) | Latino or Hispanic | did not return to baseline | 11 |
| high school grad or GED | Latino or Hispanic | did not return to baseline | 10 |
| Some college or 2 year degree (or trade or technical school) | Asian | returned to baseline | 9 |
| Some college or 2 year degree (or trade or technical school) | White Latino or Hispanic | returned to baseline | 9 |
| 4-year college graduate | Latino or Hispanic | returned to baseline | 9 |
| Some high school, but did not graduate | White | returned to baseline | 8 |
| Some college or 2 year degree (or trade or technical school) | Asian | did not return to baseline | 8 |
| Some college or 2 year degree (or trade or technical school) | Black or African American | did not return to baseline | 8 |
| high school grad or GED | Black or African American | returned to baseline | 7 |
| More than 4-year college degree | Other or multiracial | returned to baseline | 7 |
| More than 4-year college degree | Black or African American | returned to baseline | 7 |
| Some high school, but did not graduate | Latino or Hispanic | did not return to baseline | 6 |
| high school grad or GED | Indigenous | returned to baseline | 6 |
| Some college or 2 year degree (or trade or technical school) | Native Hawaiian or other Pacific Islander | returned to baseline | 6 |
| high school grad or GED | Asian | did not return to baseline | 5 |
| high school grad or GED | Asian | returned to baseline | 5 |
| 4-year college graduate | Latino or Hispanic | did not return to baseline | 5 |
| 4-year college graduate | Black or African American | returned to baseline | 5 |
| Some high school, but did not graduate | White | did not return to baseline | 4 |
| high school grad or GED | Native Hawaiian or other Pacific Islander | returned to baseline | 4 |
| high school grad or GED | White Latino or Hispanic | returned to baseline | 4 |
| Some college or 2 year degree (or trade or technical school) | Indigenous | returned to baseline | 4 |
| Some college or 2 year degree (or trade or technical school) | White Black or African American | returned to baseline | 4 |
| 4-year college graduate | Other or multiracial | returned to baseline | 4 |
| More than 4-year college degree | Latino or Hispanic | did not return to baseline | 4 |
| high school grad or GED | Other or multiracial | did not return to baseline | 3 |
| Some college or 2 year degree (or trade or technical school) | returned to baseline | 3 | |
| Some college or 2 year degree (or trade or technical school) | Other or multiracial | did not return to baseline | 3 |
| Some college or 2 year degree (or trade or technical school) | Black or African American Latino or Hispanic | returned to baseline | 3 |
| Some college or 2 year degree (or trade or technical school) | White Latino or Hispanic | did not return to baseline | 3 |
| 4-year college graduate | returned to baseline | 3 | |
| 4-year college graduate | Black or African American | did not return to baseline | 3 |
| 4-year college graduate | White Asian | returned to baseline | 3 |
| More than 4-year college degree | Indigenous | returned to baseline | 3 |
| More than 4-year college degree | White Indigenous | returned to baseline | 3 |
| More than 4-year college degree | White Asian | returned to baseline | 3 |
| NA | Latino or Hispanic | returned to baseline | 3 |
| 8th grade or less | Latino or Hispanic | did not return to baseline | 2 |
| 8th grade or less | White | returned to baseline | 2 |
| Some high school, but did not graduate | Other or multiracial | did not return to baseline | 2 |
| Some high school, but did not graduate | Indigenous | did not return to baseline | 2 |
| Some high school, but did not graduate | White Latino or Hispanic | returned to baseline | 2 |
| high school grad or GED | Native Hawaiian or other Pacific Islander | did not return to baseline | 2 |
| high school grad or GED | White Native Hawaiian or other Pacific Islander | returned to baseline | 2 |
| high school grad or GED | White Black or African American | did not return to baseline | 2 |
| Some college or 2 year degree (or trade or technical school) | Native Hawaiian or other Pacific Islander | did not return to baseline | 2 |
| Some college or 2 year degree (or trade or technical school) | White Indigenous | did not return to baseline | 2 |
| Some college or 2 year degree (or trade or technical school) | White Indigenous | returned to baseline | 2 |
| Some college or 2 year degree (or trade or technical school) | White Asian | returned to baseline | 2 |
| 4-year college graduate | White Asian | did not return to baseline | 2 |
| 4-year college graduate | White Black or African American | returned to baseline | 2 |
| More than 4-year college degree | Other or multiracial | did not return to baseline | 2 |
| More than 4-year college degree | White Asian | did not return to baseline | 2 |
| More than 4-year college degree | White Latino or Hispanic | did not return to baseline | 2 |
| More than 4-year college degree | White Black or African American | returned to baseline | 2 |
| NA | White | returned to baseline | 2 |
| 8th grade or less | did not return to baseline | 1 | |
| 8th grade or less | Asian | returned to baseline | 1 |
| 8th grade or less | Black or African American | did not return to baseline | 1 |
| Some high school, but did not graduate | Other or multiracial | returned to baseline | 1 |
| Some high school, but did not graduate | Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| Some high school, but did not graduate | Asian | did not return to baseline | 1 |
| Some high school, but did not graduate | Asian | returned to baseline | 1 |
| Some high school, but did not graduate | Latino or Hispanic Indigenous | returned to baseline | 1 |
| Some high school, but did not graduate | Black or African American | returned to baseline | 1 |
| Some high school, but did not graduate | White Latino or Hispanic | did not return to baseline | 1 |
| high school grad or GED | did not return to baseline | 1 | |
| high school grad or GED | Other or multiracial | returned to baseline | 1 |
| high school grad or GED | Latino or Hispanic Asian | did not return to baseline | 1 |
| high school grad or GED | White Indigenous | did not return to baseline | 1 |
| high school grad or GED | White Asian | returned to baseline | 1 |
| high school grad or GED | White Black or African American | returned to baseline | 1 |
| high school grad or GED | White Black or African American Asian Indigenous | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | Indigenous | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | Native Hawaiian or other Pacific Islander Indigenous | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | Latino or Hispanic Other or multiracial | returned to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | Latino or Hispanic Indigenous | returned to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Other or multiracial | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Native Hawaiian or other Pacific Islander Other or multiracial | returned to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Asian | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Asian Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Latino or Hispanic Indigenous | returned to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Black or African American | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Black or African American Indigenous | did not return to baseline | 1 |
| Some college or 2 year degree (or trade or technical school) | White Black or African American Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| 4-year college graduate | did not return to baseline | 1 | |
| 4-year college graduate | Other or multiracial | did not return to baseline | 1 |
| 4-year college graduate | Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| 4-year college graduate | Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| 4-year college graduate | White Indigenous | did not return to baseline | 1 |
| 4-year college graduate | White Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| More than 4-year college degree | Indigenous | did not return to baseline | 1 |
| More than 4-year college degree | Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| More than 4-year college degree | Asian Other or multiracial | returned to baseline | 1 |
| More than 4-year college degree | Asian Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| More than 4-year college degree | Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| More than 4-year college degree | Latino or Hispanic | returned to baseline | 1 |
| More than 4-year college degree | Latino or Hispanic Other or multiracial | did not return to baseline | 1 |
| More than 4-year college degree | Latino or Hispanic Other or multiracial | returned to baseline | 1 |
| More than 4-year college degree | Latino or Hispanic Indigenous | did not return to baseline | 1 |
| More than 4-year college degree | Latino or Hispanic Indigenous | returned to baseline | 1 |
| More than 4-year college degree | Black or African American | did not return to baseline | 1 |
| More than 4-year college degree | White Other or multiracial | did not return to baseline | 1 |
| More than 4-year college degree | White Indigenous | did not return to baseline | 1 |
| More than 4-year college degree | White Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| More than 4-year college degree | White Latino or Hispanic | returned to baseline | 1 |
| NA | returned to baseline | 1 | |
| NA | Other or multiracial | returned to baseline | 1 |
| NA | Black or African American | did not return to baseline | 1 |
| NA | White | did not return to baseline | 1 |
| NA | White Asian | returned to baseline | 1 |
kable(table_2, col.names = c("Child Race & Ethnicity","Parent Race & Ethnicity","Baseline Status", "n"), caption = "Table 2: Baseline Staus based on Parent and Child race/ethnicity")%>%
kableExtra::kable_styling(latex_options = c("striped","scale_down"))| Child Race & Ethnicity | Parent Race & Ethnicity | Baseline Status | n |
|---|---|---|---|
| White | White | returned to baseline | 433 |
| White | White | did not return to baseline | 286 |
| Latino or Hispanic | Latino or Hispanic | returned to baseline | 91 |
| Asian | Asian | returned to baseline | 47 |
| Asian | Asian | did not return to baseline | 45 |
| Black or African American | Black or African American | returned to baseline | 34 |
| Latino or Hispanic | Latino or Hispanic | did not return to baseline | 27 |
| Other or multiracial | Other or multiracial | returned to baseline | 20 |
| Other or multiracial | White | returned to baseline | 14 |
| Black or African American | Black or African American | did not return to baseline | 13 |
| White Latino or Hispanic | White Latino or Hispanic | returned to baseline | 13 |
| White Black or African American | White | returned to baseline | 11 |
| Other or multiracial | Other or multiracial | did not return to baseline | 10 |
| Other or multiracial | White | did not return to baseline | 10 |
| Indigenous | Indigenous | returned to baseline | 9 |
| Asian | White | returned to baseline | 9 |
| Native Hawaiian or other Pacific Islander | Native Hawaiian or other Pacific Islander | returned to baseline | 8 |
| Latino or Hispanic | White | returned to baseline | 8 |
| White | Latino or Hispanic | returned to baseline | 8 |
| White Asian | White | returned to baseline | 8 |
| White Latino or Hispanic | White | did not return to baseline | 8 |
| White Latino or Hispanic | White | returned to baseline | 8 |
| White Black or African American | White | did not return to baseline | 8 |
| White Black or African American | White Black or African American | returned to baseline | 8 |
| White Asian | Asian | returned to baseline | 7 |
| Asian | White | did not return to baseline | 6 |
| Latino or Hispanic | White | did not return to baseline | 6 |
| White Asian | White | did not return to baseline | 6 |
| White Asian | White Asian | returned to baseline | 6 |
| White Latino or Hispanic | Latino or Hispanic | returned to baseline | 6 |
| Native Hawaiian or other Pacific Islander | Native Hawaiian or other Pacific Islander | did not return to baseline | 5 |
| Black or African American | White | returned to baseline | 5 |
| White Indigenous | White | returned to baseline | 5 |
| White Indigenous | White Indigenous | returned to baseline | 5 |
| White Latino or Hispanic | White Latino or Hispanic | did not return to baseline | 5 |
| Other or multiracial | Asian | did not return to baseline | 4 |
| Indigenous | Indigenous | did not return to baseline | 4 |
| Black or African American Latino or Hispanic | Latino or Hispanic | returned to baseline | 4 |
| White Other or multiracial | White | returned to baseline | 4 |
| White Latino or Hispanic | Latino or Hispanic | did not return to baseline | 4 |
| returned to baseline | 3 | ||
| Latino or Hispanic | returned to baseline | 3 | |
| Other or multiracial | Asian | returned to baseline | 3 |
| Other or multiracial | Latino or Hispanic | did not return to baseline | 3 |
| Other or multiracial | Black or African American | returned to baseline | 3 |
| Black or African American Latino or Hispanic | Black or African American Latino or Hispanic | returned to baseline | 3 |
| White Indigenous | White | did not return to baseline | 3 |
| White Indigenous | White Indigenous | did not return to baseline | 3 |
| did not return to baseline | 2 | ||
| White | did not return to baseline | 2 | |
| Indigenous | Latino or Hispanic Indigenous | returned to baseline | 2 |
| Native Hawaiian or other Pacific Islander | White | returned to baseline | 2 |
| Latino or Hispanic Indigenous | Indigenous | returned to baseline | 2 |
| Black or African American | White | did not return to baseline | 2 |
| Black or African American Other or multiracial | Other or multiracial | returned to baseline | 2 |
| White | returned to baseline | 2 | |
| White | Other or multiracial | returned to baseline | 2 |
| White | Latino or Hispanic | did not return to baseline | 2 |
| White | White Latino or Hispanic | returned to baseline | 2 |
| White Asian | White Asian | did not return to baseline | 2 |
| White Latino or Hispanic Asian | White Asian | did not return to baseline | 2 |
| White Black or African American | Black or African American | returned to baseline | 2 |
| White Black or African American Other or multiracial | White | returned to baseline | 2 |
| Native Hawaiian or other Pacific Islander | returned to baseline | 1 | |
| Asian | did not return to baseline | 1 | |
| White | returned to baseline | 1 | |
| Other or multiracial | did not return to baseline | 1 | |
| Other or multiracial | Indigenous | returned to baseline | 1 |
| Other or multiracial | Latino or Hispanic Other or multiracial | returned to baseline | 1 |
| Other or multiracial | White Other or multiracial | did not return to baseline | 1 |
| Other or multiracial | White Black or African American | returned to baseline | 1 |
| Indigenous | Asian | did not return to baseline | 1 |
| Indigenous Other or multiracial | Indigenous | returned to baseline | 1 |
| Native Hawaiian or other Pacific Islander | White | did not return to baseline | 1 |
| Native Hawaiian or other Pacific Islander | White Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| Native Hawaiian or other Pacific Islander Indigenous | Native Hawaiian or other Pacific Islander Indigenous | did not return to baseline | 1 |
| Asian | returned to baseline | 1 | |
| Asian | Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| Asian Other or multiracial | Asian Other or multiracial | returned to baseline | 1 |
| Asian Native Hawaiian or other Pacific Islander | Asian | did not return to baseline | 1 |
| Asian Native Hawaiian or other Pacific Islander | Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| Latino or Hispanic | returned to baseline | 1 | |
| Latino or Hispanic | Latino or Hispanic Indigenous | returned to baseline | 1 |
| Latino or Hispanic Other or multiracial | Latino or Hispanic | did not return to baseline | 1 |
| Latino or Hispanic Other or multiracial | White | returned to baseline | 1 |
| Latino or Hispanic Indigenous Other or multiracial | Latino or Hispanic | returned to baseline | 1 |
| Latino or Hispanic Native Hawaiian or other Pacific Islander | Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| Latino or Hispanic Native Hawaiian or other Pacific Islander | Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| Latino or Hispanic Asian | Latino or Hispanic | returned to baseline | 1 |
| Latino or Hispanic Asian | Latino or Hispanic Other or multiracial | did not return to baseline | 1 |
| Latino or Hispanic Asian | Latino or Hispanic Asian | did not return to baseline | 1 |
| Black or African American Native Hawaiian or other Pacific Islander | Black or African American | returned to baseline | 1 |
| Black or African American Asian | Asian | did not return to baseline | 1 |
| Black or African American Asian | Asian | returned to baseline | 1 |
| Black or African American Latino or Hispanic | Black or African American | did not return to baseline | 1 |
| Black or African American Latino or Hispanic | Black or African American | returned to baseline | 1 |
| White | Other or multiracial | did not return to baseline | 1 |
| White | Asian | did not return to baseline | 1 |
| White | Asian | returned to baseline | 1 |
| White | White Indigenous | did not return to baseline | 1 |
| White | White Asian | returned to baseline | 1 |
| White Other or multiracial | Latino or Hispanic Other or multiracial | returned to baseline | 1 |
| White Other or multiracial | White Other or multiracial | did not return to baseline | 1 |
| White Native Hawaiian or other Pacific Islander | Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| White Native Hawaiian or other Pacific Islander | White | returned to baseline | 1 |
| White Native Hawaiian or other Pacific Islander Other or multiracial | White Native Hawaiian or other Pacific Islander Other or multiracial | returned to baseline | 1 |
| White Asian | Asian | did not return to baseline | 1 |
| White Asian Other or multiracial | Other or multiracial | returned to baseline | 1 |
| White Asian Other or multiracial | White | returned to baseline | 1 |
| White Asian Other or multiracial | White Asian | returned to baseline | 1 |
| White Asian Indigenous | White Asian | did not return to baseline | 1 |
| White Asian Native Hawaiian or other Pacific Islander | Asian Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| White Asian Native Hawaiian or other Pacific Islander | White Asian | returned to baseline | 1 |
| White Asian Native Hawaiian or other Pacific Islander | White Asian Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
| White Latino or Hispanic Other or multiracial | White | returned to baseline | 1 |
| White Latino or Hispanic Indigenous | Latino or Hispanic Indigenous | did not return to baseline | 1 |
| White Latino or Hispanic Indigenous | White Latino or Hispanic | did not return to baseline | 1 |
| White Latino or Hispanic Indigenous | White Latino or Hispanic Indigenous | returned to baseline | 1 |
| White Latino or Hispanic Native Hawaiian or other Pacific Islander | Latino or Hispanic | did not return to baseline | 1 |
| White Latino or Hispanic Native Hawaiian or other Pacific Islander Indigenous | White | did not return to baseline | 1 |
| White Latino or Hispanic Asian | White Latino or Hispanic | returned to baseline | 1 |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | White Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander Indigenous | White Asian Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| White Black or African American | White Black or African American | did not return to baseline | 1 |
| White Black or African American Indigenous | White Indigenous | did not return to baseline | 1 |
| White Black or African American Indigenous | White Native Hawaiian or other Pacific Islander | returned to baseline | 1 |
| White Black or African American Indigenous | White Black or African American Indigenous | did not return to baseline | 1 |
| White Black or African American Native Hawaiian or other Pacific Islander | White | did not return to baseline | 1 |
| White Black or African American Native Hawaiian or other Pacific Islander | White Black or African American | did not return to baseline | 1 |
| White Black or African American Asian | White Asian | returned to baseline | 1 |
| White Black or African American Asian Indigenous | White Black or African American Asian Indigenous | did not return to baseline | 1 |
| White Black or African American Latino or Hispanic | Latino or Hispanic | returned to baseline | 1 |
| White Black or African American Latino or Hispanic | White Black or African American | did not return to baseline | 1 |
| White Black or African American Latino or Hispanic Native Hawaiian or other Pacific Islander | White Black or African American Native Hawaiian or other Pacific Islander | did not return to baseline | 1 |
kable(table_3, col.names = c("Child Race & Ethnicity","Child Gender","Baseline Status","n"),caption = "Table 3: Baseline Staus based on Child race/ethnicity and Gender")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Child Race & Ethnicity | Child Gender | Baseline Status | n |
|---|---|---|---|
| White | Female | returned to baseline | 228 |
| White | Male | returned to baseline | 221 |
| White | Female | did not return to baseline | 154 |
| White | Male | did not return to baseline | 137 |
| Latino or Hispanic | Female | returned to baseline | 51 |
| Latino or Hispanic | Male | returned to baseline | 50 |
| Asian | Female | returned to baseline | 32 |
| Other or multiracial | Male | returned to baseline | 28 |
| Asian | Male | did not return to baseline | 28 |
| Asian | Male | returned to baseline | 26 |
| Asian | Female | did not return to baseline | 23 |
| Black or African American | Male | returned to baseline | 23 |
| Other or multiracial | Male | did not return to baseline | 19 |
| Latino or Hispanic | Female | did not return to baseline | 17 |
| White Black or African American | Male | returned to baseline | 17 |
| Latino or Hispanic | Male | did not return to baseline | 16 |
| Black or African American | Female | returned to baseline | 16 |
| Other or multiracial | Female | returned to baseline | 15 |
| White Latino or Hispanic | Female | returned to baseline | 14 |
| White Latino or Hispanic | Male | returned to baseline | 13 |
| White Asian | Female | returned to baseline | 12 |
| Other or multiracial | Female | did not return to baseline | 10 |
| White Asian | Male | returned to baseline | 9 |
| White Latino or Hispanic | Female | did not return to baseline | 9 |
| Indigenous | Female | returned to baseline | 8 |
| Black or African American | Male | did not return to baseline | 8 |
| White Latino or Hispanic | Male | did not return to baseline | 8 |
| Native Hawaiian or other Pacific Islander | Male | returned to baseline | 7 |
| Black or African American | Female | did not return to baseline | 7 |
| White Black or African American | Female | did not return to baseline | 7 |
| White Indigenous | Female | returned to baseline | 6 |
| White Asian | Male | did not return to baseline | 6 |
| Male | did not return to baseline | 5 | |
| Male | returned to baseline | 4 | |
| Female | returned to baseline | 4 | |
| Indigenous | Male | did not return to baseline | 4 |
| Native Hawaiian or other Pacific Islander | Male | did not return to baseline | 4 |
| Native Hawaiian or other Pacific Islander | Female | returned to baseline | 4 |
| Black or African American Latino or Hispanic | Male | returned to baseline | 4 |
| Black or African American Latino or Hispanic | Female | returned to baseline | 4 |
| White Indigenous | Male | returned to baseline | 4 |
| White Indigenous | Female | did not return to baseline | 4 |
| White Black or African American | Female | returned to baseline | 4 |
| Indigenous | Male | returned to baseline | 3 |
| White Other or multiracial | Male | returned to baseline | 3 |
| White Asian | Female | did not return to baseline | 3 |
| Native Hawaiian or other Pacific Islander | Female | did not return to baseline | 2 |
| Latino or Hispanic Indigenous | Male | returned to baseline | 2 |
| White Other or multiracial | Female | returned to baseline | 2 |
| White Indigenous | Male | did not return to baseline | 2 |
| White Asian Other or multiracial | Female | returned to baseline | 2 |
| White Asian Native Hawaiian or other Pacific Islander | Female | did not return to baseline | 2 |
| White Latino or Hispanic Indigenous | Male | did not return to baseline | 2 |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | Female | returned to baseline | 2 |
| White Black or African American | Male | did not return to baseline | 2 |
| White Black or African American Other or multiracial | Male | returned to baseline | 2 |
| White Black or African American Indigenous | Female | did not return to baseline | 2 |
| Indigenous | Female | did not return to baseline | 1 |
| Indigenous Other or multiracial | Female | returned to baseline | 1 |
| Native Hawaiian or other Pacific Islander Indigenous | Male | did not return to baseline | 1 |
| Asian Other or multiracial | Male | returned to baseline | 1 |
| Asian Native Hawaiian or other Pacific Islander | Male | did not return to baseline | 1 |
| Asian Native Hawaiian or other Pacific Islander | Female | returned to baseline | 1 |
| Latino or Hispanic Other or multiracial | Male | did not return to baseline | 1 |
| Latino or Hispanic Other or multiracial | Male | returned to baseline | 1 |
| Latino or Hispanic Indigenous Other or multiracial | Female | returned to baseline | 1 |
| Latino or Hispanic Native Hawaiian or other Pacific Islander | Male | did not return to baseline | 1 |
| Latino or Hispanic Native Hawaiian or other Pacific Islander | Male | returned to baseline | 1 |
| Latino or Hispanic Asian | Male | did not return to baseline | 1 |
| Latino or Hispanic Asian | Female | did not return to baseline | 1 |
| Latino or Hispanic Asian | Female | returned to baseline | 1 |
| Black or African American Other or multiracial | Male | returned to baseline | 1 |
| Black or African American Other or multiracial | Female | returned to baseline | 1 |
| Black or African American Native Hawaiian or other Pacific Islander | Female | returned to baseline | 1 |
| Black or African American Asian | Female | did not return to baseline | 1 |
| Black or African American Asian | Female | returned to baseline | 1 |
| Black or African American Latino or Hispanic | Male | did not return to baseline | 1 |
| White Other or multiracial | Male | did not return to baseline | 1 |
| White Native Hawaiian or other Pacific Islander | Male | returned to baseline | 1 |
| White Native Hawaiian or other Pacific Islander | Female | did not return to baseline | 1 |
| White Native Hawaiian or other Pacific Islander Other or multiracial | Male | returned to baseline | 1 |
| White Asian Other or multiracial | Male | returned to baseline | 1 |
| White Asian Indigenous | Female | did not return to baseline | 1 |
| White Asian Native Hawaiian or other Pacific Islander | Male | returned to baseline | 1 |
| White Latino or Hispanic Other or multiracial | Female | returned to baseline | 1 |
| White Latino or Hispanic Indigenous | Female | returned to baseline | 1 |
| White Latino or Hispanic Native Hawaiian or other Pacific Islander | Male | did not return to baseline | 1 |
| White Latino or Hispanic Native Hawaiian or other Pacific Islander Indigenous | Male | did not return to baseline | 1 |
| White Latino or Hispanic Asian | Male | did not return to baseline | 1 |
| White Latino or Hispanic Asian | Male | returned to baseline | 1 |
| White Latino or Hispanic Asian | Female | did not return to baseline | 1 |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander Indigenous | Male | returned to baseline | 1 |
| White Black or African American Indigenous | Female | returned to baseline | 1 |
| White Black or African American Native Hawaiian or other Pacific Islander | Male | did not return to baseline | 1 |
| White Black or African American Native Hawaiian or other Pacific Islander | Female | did not return to baseline | 1 |
| White Black or African American Asian | Female | returned to baseline | 1 |
| White Black or African American Asian Indigenous | Female | did not return to baseline | 1 |
| White Black or African American Latino or Hispanic | Male | did not return to baseline | 1 |
| White Black or African American Latino or Hispanic | Male | returned to baseline | 1 |
| White Black or African American Latino or Hispanic Native Hawaiian or other Pacific Islander | Male | did not return to baseline | 1 |
kable(table_4,col.names = c("Interpretor Need","Language","Baseline Status","n"), caption = " Table 4:Baseline Staus based on Interpretor need and Language")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Interpretor Need | Language | Baseline Status | n |
|---|---|---|---|
| No | English | returned to baseline | 786 |
| No | English | did not return to baseline | 484 |
| Yes | Spanish | returned to baseline | 34 |
| No | Spanish | returned to baseline | 12 |
| No | Spanish | did not return to baseline | 6 |
| Yes | English | returned to baseline | 5 |
| Yes | Spanish | did not return to baseline | 5 |
| Yes | English | did not return to baseline | 3 |
| No | Vietnamese | did not return to baseline | 2 |
| No | Chinese | returned to baseline | 1 |
| No | Somali | returned to baseline | 1 |
| Yes | Vietnamese | returned to baseline | 1 |
| Yes | Chinese | did not return to baseline | 1 |
| Yes | Chinese | returned to baseline | 1 |
| NA | English | did not return to baseline | 1 |
| NA | English | returned to baseline | 1 |
Tables as instructed
Language
table.lan <-qol_final %>%
tabyl(interviewlang_change, `Back to Baseline`) %>%
adorn_totals(c("row", "col")) %>%
adorn_percentages("row") %>%
adorn_pct_formatting(rounding = "half up", digits = 0) %>%
adorn_ns()
knitr::kable(table.lan,col.names = c("Language","No return to baseline","Return to baseline","Totals"), caption = " Table 5:Language and Baseline")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Language | No return to baseline | Return to baseline | Totals |
|---|---|---|---|
| English | 38% (488) | 62% (792) | 100% (1280) |
| Spanish | 19% (11) | 81% (46) | 100% (57) |
| Vietnamese | 67% (2) | 33% (1) | 100% (3) |
| Chinese | 33% (1) | 67% (2) | 100% (3) |
| Somali | 0% (0) | 100% (1) | 100% (1) |
| Total | 37% (502) | 63% (842) | 100% (1344) |
Interpretor used
table.int <-qol_final %>%
tabyl(interp_needed, `Back to Baseline`) %>%
adorn_totals(c("row", "col")) %>%
adorn_percentages("row") %>%
adorn_pct_formatting(rounding = "half up", digits = 0) %>%
adorn_ns()
knitr::kable(table.int,col.names = c("Interpreter","No return to baseline","Return to baseline","Totals"), caption = " Table 6:Interpreter need and Baseline")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Interpreter | No return to baseline | Return to baseline | Totals |
|---|---|---|---|
| No | 38% (492) | 62% (800) | 100% (1292) |
| Yes | 18% (9) | 82% (41) | 100% (50) |
| NA | 50% (1) | 50% (1) | 100% (2) |
| Total | 37% (502) | 63% (842) | 100% (1344) |
Parent Education
table.edu <-qol_final %>%
tabyl(education, `Back to Baseline`) %>%
adorn_totals(c("row", "col")) %>%
adorn_percentages("row") %>%
adorn_pct_formatting(rounding = "half up", digits = 0) %>%
adorn_ns()
knitr::kable(table.edu,col.names = c("Education level","No return to baseline","Return to baseline","Totals"), caption = " Table 7: Education and Baseline")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Education level | No return to baseline | Return to baseline | Totals |
|---|---|---|---|
| 8th grade or less | 17% (4) | 83% (20) | 100% (24) |
| Some high school, but did not graduate | 30% (17) | 70% (39) | 100% (56) |
| high school grad or GED | 41% (77) | 59% (111) | 100% (188) |
| Some college or 2 year degree (or trade or technical school) | 32% (133) | 68% (281) | 100% (414) |
| 4-year college graduate | 39% (135) | 61% (215) | 100% (350) |
| More than 4-year college degree | 44% (134) | 56% (168) | 100% (302) |
| NA | 20% (2) | 80% (8) | 100% (10) |
| Total | 37% (502) | 63% (842) | 100% (1344) |
Parent R&E
table.pre <-qol_final %>%
tabyl(r.e.parent, `Back to Baseline`) %>%
adorn_totals(c("row", "col")) %>%
adorn_percentages("row") %>%
adorn_pct_formatting(rounding = "half up", digits = 0) %>%
adorn_ns()
knitr::kable(table.pre,col.names = c("Race and or Ethnicity","No return to baseline","Return to baseline","Totals"), caption = " Table 8:Parent Race and or Ethnicity and Baseline")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Race and or Ethnicity | No return to baseline | Return to baseline | Totals |
|---|---|---|---|
| 30% (3) | 70% (7) | 100% (10) | |
| Other or multiracial | 31% (11) | 69% (25) | 100% (36) |
| Indigenous | 24% (4) | 76% (13) | 100% (17) |
| Native Hawaiian or other Pacific Islander | 41% (7) | 59% (10) | 100% (17) |
| Native Hawaiian or other Pacific Islander Indigenous | 100% (1) | 0% (0) | 100% (1) |
| Asian | 48% (55) | 52% (59) | 100% (114) |
| Asian Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| Asian Native Hawaiian or other Pacific Islander | 33% (1) | 67% (2) | 100% (3) |
| Latino or Hispanic | 25% (38) | 75% (115) | 100% (153) |
| Latino or Hispanic Other or multiracial | 33% (1) | 67% (2) | 100% (3) |
| Latino or Hispanic Indigenous | 25% (1) | 75% (3) | 100% (4) |
| Latino or Hispanic Asian | 100% (1) | 0% (0) | 100% (1) |
| Black or African American | 25% (14) | 75% (41) | 100% (55) |
| Black or African American Latino or Hispanic | 0% (0) | 100% (3) | 100% (3) |
| White | 40% (340) | 60% (514) | 100% (854) |
| White Other or multiracial | 100% (2) | 0% (0) | 100% (2) |
| White Indigenous | 50% (5) | 50% (5) | 100% (10) |
| White Native Hawaiian or other Pacific Islander | 0% (0) | 100% (2) | 100% (2) |
| White Native Hawaiian or other Pacific Islander Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| White Asian | 33% (5) | 67% (10) | 100% (15) |
| White Asian Native Hawaiian or other Pacific Islander | 33% (1) | 67% (2) | 100% (3) |
| White Latino or Hispanic | 27% (6) | 73% (16) | 100% (22) |
| White Latino or Hispanic Indigenous | 0% (0) | 100% (1) | 100% (1) |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | 0% (0) | 100% (1) | 100% (1) |
| White Black or African American | 25% (3) | 75% (9) | 100% (12) |
| White Black or African American Indigenous | 100% (1) | 0% (0) | 100% (1) |
| White Black or African American Native Hawaiian or other Pacific Islander | 100% (1) | 0% (0) | 100% (1) |
| White Black or African American Asian Indigenous | 100% (1) | 0% (0) | 100% (1) |
| Total | 37% (502) | 63% (842) | 100% (1344) |
Child R&E
table.cre <-qol_final %>%
tabyl(r.e.child, `Back to Baseline`) %>%
adorn_totals(c("row", "col")) %>%
adorn_percentages("row") %>%
adorn_pct_formatting(rounding = "half up", digits = 0) %>%
adorn_ns()
knitr::kable(table.cre,col.names = c("Race and or Ethnicity","No return to baseline","Return to baseline","Totals"), caption = " Table 9:Child Race and or Ethnicity and Baseline")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Race and or Ethnicity | No return to baseline | Return to baseline | Totals |
|---|---|---|---|
| 38% (5) | 62% (8) | 100% (13) | |
| Other or multiracial | 40% (29) | 60% (43) | 100% (72) |
| Indigenous | 31% (5) | 69% (11) | 100% (16) |
| Indigenous Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| Native Hawaiian or other Pacific Islander | 35% (6) | 65% (11) | 100% (17) |
| Native Hawaiian or other Pacific Islander Indigenous | 100% (1) | 0% (0) | 100% (1) |
| Asian | 47% (51) | 53% (58) | 100% (109) |
| Asian Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| Asian Native Hawaiian or other Pacific Islander | 50% (1) | 50% (1) | 100% (2) |
| Latino or Hispanic | 25% (33) | 75% (101) | 100% (134) |
| Latino or Hispanic Other or multiracial | 50% (1) | 50% (1) | 100% (2) |
| Latino or Hispanic Indigenous | 0% (0) | 100% (2) | 100% (2) |
| Latino or Hispanic Indigenous Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| Latino or Hispanic Native Hawaiian or other Pacific Islander | 50% (1) | 50% (1) | 100% (2) |
| Latino or Hispanic Asian | 67% (2) | 33% (1) | 100% (3) |
| Black or African American | 28% (15) | 72% (39) | 100% (54) |
| Black or African American Other or multiracial | 0% (0) | 100% (2) | 100% (2) |
| Black or African American Native Hawaiian or other Pacific Islander | 0% (0) | 100% (1) | 100% (1) |
| Black or African American Asian | 50% (1) | 50% (1) | 100% (2) |
| Black or African American Latino or Hispanic | 11% (1) | 89% (8) | 100% (9) |
| White | 39% (291) | 61% (449) | 100% (740) |
| White Other or multiracial | 17% (1) | 83% (5) | 100% (6) |
| White Indigenous | 38% (6) | 63% (10) | 100% (16) |
| White Native Hawaiian or other Pacific Islander | 50% (1) | 50% (1) | 100% (2) |
| White Native Hawaiian or other Pacific Islander Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| White Asian | 30% (9) | 70% (21) | 100% (30) |
| White Asian Other or multiracial | 0% (0) | 100% (3) | 100% (3) |
| White Asian Indigenous | 100% (1) | 0% (0) | 100% (1) |
| White Asian Native Hawaiian or other Pacific Islander | 67% (2) | 33% (1) | 100% (3) |
| White Latino or Hispanic | 39% (17) | 61% (27) | 100% (44) |
| White Latino or Hispanic Other or multiracial | 0% (0) | 100% (1) | 100% (1) |
| White Latino or Hispanic Indigenous | 67% (2) | 33% (1) | 100% (3) |
| White Latino or Hispanic Native Hawaiian or other Pacific Islander | 100% (1) | 0% (0) | 100% (1) |
| White Latino or Hispanic Native Hawaiian or other Pacific Islander Indigenous | 100% (1) | 0% (0) | 100% (1) |
| White Latino or Hispanic Asian | 67% (2) | 33% (1) | 100% (3) |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander | 0% (0) | 100% (2) | 100% (2) |
| White Latino or Hispanic Asian Native Hawaiian or other Pacific Islander Indigenous | 0% (0) | 100% (1) | 100% (1) |
| White Black or African American | 30% (9) | 70% (21) | 100% (30) |
| White Black or African American Other or multiracial | 0% (0) | 100% (2) | 100% (2) |
| White Black or African American Indigenous | 67% (2) | 33% (1) | 100% (3) |
| White Black or African American Native Hawaiian or other Pacific Islander | 100% (2) | 0% (0) | 100% (2) |
| White Black or African American Asian | 0% (0) | 100% (1) | 100% (1) |
| White Black or African American Asian Indigenous | 100% (1) | 0% (0) | 100% (1) |
| White Black or African American Latino or Hispanic | 50% (1) | 50% (1) | 100% (2) |
| White Black or African American Latino or Hispanic Native Hawaiian or other Pacific Islander | 100% (1) | 0% (0) | 100% (1) |
| Total | 37% (502) | 63% (842) | 100% (1344) |
Child Gender
table.cge<-qol_final %>%
tabyl(childgender, `Back to Baseline`) %>%
adorn_totals(c("row", "col")) %>%
adorn_percentages("row") %>%
adorn_pct_formatting(rounding = "half up", digits = 0) %>%
adorn_ns()
knitr::kable(table.cge,col.names = c("Gender Identity","No return to baseline","Return to baseline","Totals"), caption = " Table 10: Child Gender Identity and Baseline")%>%
kableExtra::kable_styling(latex_options = c("striped", "scale_down"))| Gender Identity | No return to baseline | Return to baseline | Totals |
|---|---|---|---|
| Male | 37% (254) | 63% (427) | 100% (681) |
| Female | 37% (248) | 63% (415) | 100% (663) |
| Other |
|
|
100% (0) |
| Total | 37% (502) | 63% (842) | 100% (1344) |
Univariable analysis
Summary Statistics For baseline actual number
x<-QOL.Equity.Exploraton$Baseline.Actual
#find mean
mean(x)## [1] 8.723239#find median
median(x)## [1] 7.80506#find range
max(x) - min(x)## [1] 137.7259#find interquartile range (spread of middle 50% of values)
IQR(x)## [1] 18.47826#find standard deviation
sd(x)## [1] 16.72735Charts
#frequency table
table(x)## x
## -55.5830039525692 -54.3478260869565 -51.2907608695652 -48.7154150197628
## 1 1 1 1
## -47.6190476190476 -43.4782608695652 -42.8571428571429 -42.3076923076923
## 1 1 1 1
## -40.0724637681159 -39.4736842105263 -39.2857142857143 -39.1304347826087
## 1 1 3 1
## -38.4615384615385 -38.1578947368421 -36.9565217391304 -35.7142857142857
## 1 1 1 2
## -35.3260869565217 -34.7826086956522 -34.2650103519669 -34.0301003344482
## 1 1 1 1
## -33.695652173913 -32.1428571428572 -32.1428571428571 -31.6425120772947
## 1 1 2 1
## -31.3186813186813 -30.4347826086957 -30.4347826086956 -30.2631578947368
## 1 1 1 1
## -28.2608695652174 -28.0797101449275 -27.9150197628459 -27.7717391304348
## 1 1 1 1
## -26.9230769230769 -25.5952380952381 -25 -24.7584541062802
## 1 1 8 1
## -23.6842105263158 -22.3684210526316 -22.2222222222222 -21.7728758169935
## 1 1 1 1
## -21.7391304347826 -21.4285714285714 -20.8333333333333 -20.7093821510298
## 3 4 1 1
## -20.6521739130435 -19.3478260869565 -18.9538043478261 -18.9230343300111
## 1 1 1 1
## -18.4782608695652 -18.1585677749361 -17.9606625258799 -17.8571428571429
## 3 1 1 4
## -17.4242424242424 -17.3913043478261 -17.0454545454545 -16.5760869565217
## 1 4 1 1
## -16.304347826087 -15.9722222222222 -15.8200734394125 -15.5555555555556
## 2 1 1 1
## -15.3846153846154 -15.2173913043478 -15 -14.546783625731
## 1 2 1 1
## -14.2857142857143 -14.2690058479532 -14.1304347826087 -13.9130434782609
## 10 1 2 1
## -13.3333333333333 -13.0434782608696 -12.9795396419437 -12.9563492063492
## 1 2 1 1
## -12.8811369509044 -12.796442687747 -12.0879120879121 -11.9565217391304
## 1 1 1 2
## -11.8421052631579 -11.5384615384615 -11.3636363636364 -11.1111111111111
## 1 1 1 1
## -10.8695652173913 -10.7193732193732 -10.7142857142857 -10.3260869565217
## 7 1 10 1
## -9.78260869565218 -9.78260869565217 -9.72222222222221 -9.53557312252964
## 1 2 1 1
## -9.44444444444444 -9.33794466403162 -9.23913043478261 -9.21052631578947
## 1 1 1 1
## -9.17874396135266 -9.09090909090909 -9.05797101449276 -8.69565217391305
## 1 1 1 2
## -8.69565217391304 -8.53535353535354 -8.53174603174602 -8.40909090909091
## 1 1 1 1
## -8.31202046035806 -8.01435406698565 -7.95454545454545 -7.69230769230769
## 1 1 1 1
## -7.60869565217391 -7.50517598343686 -7.22222222222223 -7.14285714285715
## 4 1 1 3
## -7.14285714285714 -6.94444444444446 -6.8840579710145 -6.81818181818183
## 11 1 1 1
## -6.81818181818181 -6.78571428571429 -6.64682539682541 -6.52173913043478
## 1 1 1 3
## -6.40096618357488 -6.34057971014494 -6.32411067193676 -6.28019323671498
## 1 1 1 1
## -6.25 -6.15942028985506 -6.1212814645309 -5.94629156010231
## 2 1 1 1
## -5.93434343434343 -5.68181818181819 -5.43478260869566 -5.37439613526571
## 1 1 4 1
## -5.26315789473684 -5.2197802197802 -5.09153318077803 -5
## 1 1 1 2
## -4.86111111111111 -4.78632478632478 -4.53964194373401 -4.34782608695653
## 4 1 1 3
## -4.34782608695652 -4.16666666666667 -3.94736842105263 -3.92512077294685
## 5 1 1 1
## -3.88888888888889 -3.84615384615385 -3.73641304347827 -3.57142857142858
## 1 1 1 2
## -3.57142857142857 -3.47222222222221 -3.44202898550724 -3.40909090909091
## 10 1 1 1
## -3.33333333333333 -3.30882352941177 -3.26086956521739 -3.07971014492755
## 1 1 4 1
## -2.94486215538846 -2.93650793650794 -2.77777777777779 -2.77777777777777
## 1 1 2 2
## -2.65700483091787 -2.63157894736842 -2.63157894736841 -2.53623188405797
## 1 2 2 1
## -2.47584541062802 -2.47252747252747 -2.3989898989899 -2.29468599033817
## 1 1 1 1
## -2.27272727272727 -2.1978021978022 -2.17391304347827 -2.17391304347825
## 2 1 4 1
## -2.0933014354067 -2.08333333333334 -2.03349282296651 -1.97368421052632
## 1 2 1 1
## -1.94805194805195 -1.93236714975845 -1.65441176470588 -1.55502392344498
## 1 1 1 1
## -1.47058823529412 -1.38888888888889 -1.31578947368421 -1.23306233062331
## 1 5 2 1
## -1.13636363636364 -1.11111111111111 -1.08695652173914 -1.08695652173913
## 2 1 2 4
## -1.07142857142857 -0.905797101449281 -0.889328063241109 -0.793650793650784
## 1 2 2 1
## -0.785024154589372 -0.694444444444457 -0.694444444444443 -0.642292490118578
## 1 1 1 1
## -0.555555555555557 -0.538277511961724 -0.47846889952153 -0.30193236714976
## 2 1 1 1
## -0.27472527472527 -0.232919254658384 -0.181159420289855 -0.179425837320565
## 1 1 1 1
## -0.155279503105589 0 0.120772946859901 0.27472527472527
## 1 46 1 1
## 0.296442687747039 0.345849802371546 0.418660287081352 0.494071146245062
## 1 1 1 1
## 0.549450549450555 0.694444444444443 0.839920948616594 0.877192982456151
## 1 3 1 1
## 0.938086303939954 0.93873517786561 0.988142292490124 1.07655502392345
## 1 1 1 1
## 1.08695652173913 1.08695652173914 1.11111111111111 1.13636363636363
## 9 4 2 2
## 1.13636363636364 1.21564482029599 1.31578947368421 1.31578947368422
## 6 1 1 3
## 1.38888888888889 1.3888888888889 1.58862876254182 1.60183066361556
## 3 1 1 1
## 1.74603174603175 1.87908496732027 1.94805194805195 2.08333333333333
## 1 1 1 4
## 2.08333333333334 2.09030100334448 2.17391304347825 2.17391304347827
## 1 1 4 7
## 2.19298245614036 2.22222222222221 2.23429951690821 2.27272727272727
## 1 3 2 2
## 2.27272727272728 2.39234449760767 2.47252747252747 2.53968253968254
## 2 1 1 1
## 2.56410256410257 2.63157894736842 2.66798418972331 2.74725274725274
## 1 8 1 1
## 2.76679841897233 2.77777777777777 2.77777777777779 2.80320366132723
## 1 1 2 1
## 3.11004784688995 3.21146245059288 3.26086956521739 3.28282828282829
## 1 1 14 1
## 3.33333333333333 3.40909090909091 3.40909090909092 3.43253968253968
## 2 4 3 1
## 3.47222222222221 3.47222222222223 3.5024154589372 3.57142857142857
## 1 2 1 11
## 3.57142857142858 3.66161616161615 3.84615384615384 3.84615384615385
## 2 1 1 2
## 3.88888888888889 3.92512077294685 3.94385026737968 3.94736842105263
## 1 1 1 2
## 4.12087912087912 4.16666666666666 4.16666666666667 4.20190274841437
## 1 1 1 1
## 4.22705314009661 4.25064599483204 4.26065162907268 4.34782608695652
## 1 1 1 11
## 4.34782608695653 4.36507936507937 4.43722943722943 4.44444444444444
## 5 1 1 1
## 4.54545454545455 4.63709677419355 4.8611111111111 4.86111111111111
## 3 1 1 1
## 4.9641148325359 4.97835497835498 5.20594965675058 5.22875816993465
## 1 1 1 1
## 5.26315789473685 5.41666666666667 5.43478260869565 5.43478260869566
## 1 1 1 8
## 5.55555555555556 5.6159420289855 5.68181818181817 5.68181818181819
## 5 1 3 6
## 5.74494949494949 5.97826086956522 6.1111111111111 6.11111111111111
## 1 1 1 2
## 6.11918604651163 6.13095238095238 6.21980676328502 6.25
## 1 1 1 1
## 6.31868131868131 6.42857142857143 6.52173913043478 6.52173913043479
## 1 1 9 1
## 6.57894736842105 6.5934065934066 6.62055335968378 6.63875598086124
## 4 2 1 1
## 6.64961636828644 6.65760869565217 6.781045751634 6.81818181818181
## 1 1 1 6
## 6.87799043062201 6.90359477124183 6.94444444444444 7.03282828282829
## 1 1 2 1
## 7.10702341137123 7.14285714285714 7.14285714285715 7.22222222222221
## 1 15 5 1
## 7.22222222222223 7.32323232323233 7.38636363636364 7.57575757575758
## 1 1 1 1
## 7.60869565217391 7.60869565217392 7.63888888888889 7.6388888888889
## 11 2 3 1
## 7.69230769230769 7.70025839793281 7.79761904761904 7.8125
## 2 1 1 1
## 7.86749482401657 7.89473684210526 7.89473684210527 7.91316526610645
## 1 1 1 1
## 7.95454545454545 8.03140096618357 8.09178743961353 8.24175824175825
## 5 1 1 1
## 8.24808184143224 8.33333333333333 8.33333333333334 8.42013888888889
## 1 3 2 1
## 8.44861660079051 8.58123569794051 8.69565217391303 8.69565217391305
## 1 1 3 14
## 8.79120879120877 8.88888888888889 8.8888888888889 8.97129186602871
## 1 1 1 1
## 9.02777777777777 9.02777777777779 9.04933481152993 9.06593406593407
## 2 1 1 1
## 9.09090909090909 9.1183574879227 9.21052631578948 9.25324675324676
## 4 1 2 1
## 9.26587301587301 9.35990338164251 9.52380952380952 9.59079283887468
## 1 1 1 1
## 9.72222222222223 9.78260869565217 9.78260869565219 9.86842105263158
## 3 9 1 1
## 9.88142292490119 10 10.024154589372 10.0296442687747
## 1 4 1 1
## 10.1648351648352 10.2272727272727 10.4166666666667 10.4395604395605
## 1 5 2 1
## 10.479797979798 10.5263157894737 10.5555555555556 10.7142857142857
## 1 2 3 14
## 10.8695652173913 10.8766233766234 10.9431524547804 10.997442455243
## 7 1 1 1
## 11.1111111111111 11.2723214285714 11.292270531401 11.3636363636364
## 1 1 1 2
## 11.5079365079365 11.5338164251208 11.5384615384615 11.5451388888889
## 1 1 1 1
## 11.6600790513834 11.8055555555556 11.8181818181818 11.8421052631579
## 1 1 1 3
## 11.8589743589744 11.9318181818182 11.9565217391304 12.0879120879121
## 1 1 16 2
## 12.1411483253588 12.1753246753247 12.1825396825397 12.2222222222222
## 1 1 1 2
## 12.266081871345 12.3188405797101 12.4368686868687 12.4396135265701
## 1 1 1 1
## 12.5 12.5286041189931 12.6811594202898 12.7415458937198
## 9 1 1 1
## 12.796442687747 12.9032258064516 12.9551820728291 12.9940711462451
## 1 1 1 1
## 13.0434782608696 13.1944444444444 13.1944444444445 13.3333333333333
## 8 1 1 2
## 13.4615384615385 13.5265700483092 13.6363636363636 13.656330749354
## 1 1 5 1
## 13.6742424242424 13.8198757763975 13.8383838383838 13.8888888888889
## 1 1 1 2
## 14.1304347826087 14.2857142857143 14.4736842105263 14.5604395604396
## 12 19 1 1
## 14.6135265700483 14.7727272727273 14.9154589371981 15
## 1 6 1 2
## 15.2173913043478 15.2777777777778 15.3846153846154 15.3968253968254
## 7 3 1 1
## 15.5555555555556 15.7296650717703 15.7894736842105 15.9090909090909
## 1 1 2 2
## 15.9722222222222 16.0714285714286 16.1111111111111 16.2008281573499
## 1 1 3 1
## 16.2087912087912 16.304347826087 16.4835164835165 16.6501976284585
## 2 2 2 1
## 16.6666666666667 17.0454545454545 17.0480549199085 17.0652173913043
## 5 1 1 1
## 17.1052631578947 17.1195652173913 17.2846889952153 17.3611111111111
## 2 1 1 4
## 17.3913043478261 17.4901185770751 17.5271739130435 17.5724637681159
## 7 1 1 1
## 17.7536231884058 17.7865612648221 17.8571428571428 17.8571428571429
## 1 2 2 11
## 18.0555555555556 18.1266149870801 18.1818181818182 18.2312252964427
## 5 1 1 1
## 18.3333333333333 18.4065934065934 18.4210526315789 18.421052631579
## 2 1 1 2
## 18.4782608695652 18.5326086956522 18.8888888888889 18.968253968254
## 14 1 1 1
## 19.2307692307692 19.4246031746032 19.4444444444444 19.4444444444445
## 1 1 4 1
## 19.5054945054945 19.5652173913043 19.7463768115942 19.9007936507937
## 1 4 1 1
## 20 20.0549450549451 20.1298701298701 20.137299771167
## 2 2 1 1
## 20.1388888888889 20.1612903225807 20.2597402597403 20.2751196172249
## 2 1 1 1
## 20.4545454545455 20.5917874396135 20.6521739130435 20.6766917293233
## 4 1 7 1
## 20.7729468599034 20.8333333333333 21.0144927536232 21.0227272727273
## 1 3 1 1
## 21.2301587301587 21.2466124661247 21.4285714285714 21.4975845410628
## 1 1 10 1
## 21.5079365079365 21.5277777777778 21.5615615615616 21.5909090909091
## 1 1 1 2
## 21.6666666666667 21.7391304347826 21.8599033816425 22.1230158730159
## 1 9 1 1
## 22.1825396825397 22.2222222222222 22.3684210526316 22.4120082815735
## 1 5 1 1
## 22.6190476190476 22.6982097186701 22.7717391304348 22.7777777777778
## 1 1 1 1
## 22.790404040404 22.8260869565217 23.1547619047619 23.2213438735178
## 1 8 1 1
## 23.3333333333333 23.3893557422969 23.4989648033126 23.6111111111111
## 2 1 1 1
## 23.6413043478261 23.792270531401 23.8142292490119 23.8888888888889
## 1 1 1 1
## 23.9130434782609 24.1071428571429 24.3055555555556 24.3961352657005
## 10 1 1 2
## 24.4444444444444 24.4617224880383 24.5426829268293 24.5454545454545
## 1 2 1 1
## 24.7529644268775 24.7961956521739 25 25.3342245989305
## 1 1 12 1
## 25.5494505494506 25.5555555555556 25.6944444444444 26.0869565217391
## 1 2 4 3
## 26.1111111111111 26.1363636363636 26.3888888888889 26.4414414414414
## 1 1 2 1
## 26.7460317460317 26.8280632411067 27.0289855072464 27.1739130434783
## 1 1 1 3
## 27.2222222222222 27.2727272727273 27.328431372549 27.6315789473684
## 1 1 1 1
## 27.7777777777778 28.021978021978 28.2608695652174 28.2967032967033
## 2 1 4 1
## 28.3333333333333 28.4722222222222 28.5479797979798 28.5714285714286
## 1 1 1 4
## 28.8398692810458 29.1208791208791 29.1666666666667 29.3478260869565
## 1 1 1 4
## 29.3650793650794 29.5893719806763 29.6620046620047 29.7430830039526
## 1 1 1 1
## 29.8214285714286 29.8611111111111 30.3661616161616 30.4347826086956
## 1 1 1 1
## 30.4347826086957 30.5555555555556 30.7264957264957 30.9009009009009
## 1 1 1 1
## 31.1076604554865 31.1111111111111 31.1274509803922 31.2799043062201
## 1 1 1 1
## 31.3664596273292 31.4285714285714 31.5217391304348 31.7768199233716
## 1 1 2 1
## 31.8181818181818 31.9444444444444 32.1428571428571 32.5
## 1 2 5 1
## 32.6086956521739 32.6604554865424 32.8557312252964 32.9545454545455
## 6 1 1 3
## 33.2417582417582 33.3333333333333 33.5240274599542 33.695652173913
## 1 2 1 3
## 33.8768115942029 34.0277777777778 34.6153846153846 34.7222222222222
## 1 1 2 1
## 34.7826086956522 34.963768115942 35.0931677018634 35.1010101010101
## 2 2 1 1
## 35.2941176470588 35.6280193236715 35.7142857142857 35.8695652173913
## 1 1 1 2
## 36.3636363636364 36.9565217391304 37.2122762148338 37.4505928853755
## 1 2 1 1
## 37.593984962406 37.598814229249 37.7717391304348 38.0434782608696
## 1 2 1 1
## 38.2748538011696 38.4615384615385 39.1304347826087 39.2156862745098
## 1 1 2 1
## 39.2857142857143 40.2173913043478 40.3409090909091 40.9090909090909
## 2 1 1 1
## 41.1067193675889 41.304347826087 41.6666666666667 42.032967032967
## 1 1 1 1
## 42.0454545454545 42.3913043478261 42.4812030075188 42.8571428571429
## 1 3 1 1
## 43.0357142857143 43.4782608695652 43.5770750988142 44.0476190476191
## 1 5 1 1
## 44.4444444444444 44.7463768115942 45 45.1470588235294
## 1 1 1 1
## 45.4545454545455 45.6521739130435 46.4285714285714 46.4371980676329
## 1 1 2 1
## 46.5909090909091 47.9166666666667 48.2707509881423 48.3585858585859
## 1 1 1 1
## 48.7698412698413 48.9130434782609 50 50.5847953216374
## 1 2 3 1
## 51.6983695652174 51.9246031746032 52.1739130434783 53.2608695652174
## 1 1 1 2
## 54.8015873015873 57.1428571428571 60.7142857142857 63.0434782608696
## 1 1 1 1
## 80 82.1428571428571
## 1 1#boxplot
boxplot(x)
#histogram
hist(x)
#density curve
plot(density(x))