R/medianAgeTab.R
In ColoradoDemography/codemogLib:
Defines functions
medianAgeTab
#' medianAgeTab Creates table showing the Median Age by Gender
#' for a selected place and county or for a copunty and for the state
#'
#' @param listID the list containing place id and Place names
#' @param ACS a string identifying the input dataset eg: "acs1115"
#' @param state the State FIPS code, defaluts to "08" for Colorado.
#' @param oType type of output, html or latex
#' @return a formatted table and dataset
#' @export
medianAgeTab <- function(listID, ACS, oType, state="08"){
# Collecting place ids from idList, setting default values
ctyfips <- listID$ctyNum
ctyname <- listID$ctyName
placefips <- listID$plNum
placename <- listID$plName
# if(listID$PlFilter == "T") {
# placefips <- ""
# placename <- ""
# }
#County Age
medAgecty <- codemog_api(data="b01002",db=ACS, geonum=paste("1", state, ctyfips, sep=""), meta="no")
medAgectyMOE <- codemog_api(data="b01002_moe",db=ACS, geonum=paste("1", state, ctyfips, sep=""), meta="no")
medAgecty2 <- gather(medAgecty[1,8:10])
medAgecty2$key <- c("Total","Male","Female")
names(medAgecty2)[2] <- "MedAge_c"
medAgecty2MOE <- gather(medAgectyMOE[1,8:10])
medAgecty2MOE$key <- c("Total","Male","Female")
names(medAgecty2MOE)[2] <- "MOE_c"
f.ctyAge <- merge(medAgecty2, medAgecty2MOE, by = "key")
#State Age
medAgeST <- codemog_api(data="b01002",db=ACS, geonum=paste("1", state, sep=""), meta="no")
medAgeSTMOE <- codemog_api(data="b01002_moe",db=ACS, geonum=paste("1", state, sep=""), meta="no")
medAgeST2 <- gather(medAgeST[1,8:10])
medAgeST2$key <- c("Total","Male","Female")
names(medAgeST2)[2] <- "MedAge_s"
medAgeST2MOE <- gather(medAgeSTMOE[1,8:10])
medAgeST2MOE$key <- c("Total","Male","Female")
names(medAgeST2MOE)[2] <- "MOE_s"
f.stateAge <- merge(medAgeST2, medAgeST2MOE, by = "key")
if(nchar(placefips) != 0) {
#place Age
medAgeplace <- codemog_api(data="b01002",db=ACS, geonum=paste("1", state, placefips, sep=""), meta="no")
medAgeplaceMOE <- codemog_api(data="b01002_moe",db=ACS, geonum=paste("1", state, placefips, sep=""), meta="no")
medAgeplace2 <- gather(medAgeplace[1,8:10])
medAgeplace2$key <- c("Total","Male","Female")
names(medAgeplace2)[2] <- "MedAge_p"
medAgeplace2MOE <- gather(medAgeplaceMOE[1,8:10])
medAgeplace2MOE$key <- c("Total","Male","Female")
names(medAgeplace2MOE)[2] <- "MOE_p"
f.placeAge <- merge(medAgeplace2, medAgeplace2MOE, by = "key")
}
#Creating Copmbined table and Calcualting tests
if(nchar(placefips) == 0) {
f.ageTab <- merge(f.ctyAge, f.stateAge, by = "key")
#Calculating significant differences
f.ageTab$MedAge_c <- as.numeric(f.ageTab$MedAge_c)
f.ageTab$MOE_c <- as.numeric(f.ageTab$MOE_c)
f.ageTab$MedAge_s <- as.numeric(f.ageTab$MedAge_s)
f.ageTab$MOE_s <- as.numeric(f.ageTab$MOE_s)
f.ageTab$ZScore <- (abs(f.ageTab$MedAge_c - f.ageTab$MedAge_s)/
sqrt((f.ageTab$MOE_c^2) + (f.ageTab$MOE_s^2)))
f.ageTab$Sig_Diff <- ifelse(f.ageTab$ZScore < 1,"No","Yes")
f.ageTab$Difference <- ifelse(f.ageTab$Sig_Diff == "Yes", ifelse(f.ageTab$MedAge_c < f.ageTab$MedAge_s,"Younger","Older"),"")
m.ageTab <- as.matrix(f.ageTab[,c(1:5,7,8)])
} else {
f.ageTab <- merge(f.placeAge, f.ctyAge, by = "key")
#Calculating significant differences
f.ageTab$MedAge_p <- as.numeric(f.ageTab$MedAge_p)
f.ageTab$MOE_p <- as.numeric(f.ageTab$MOE_p)
f.ageTab$MedAge_c <- as.numeric(f.ageTab$MedAge_c)
f.ageTab$MOE_c <- as.numeric(f.ageTab$MOE_c)
f.ageTab$ZScore <- (abs(f.ageTab$MedAge_p - f.ageTab$MedAge_c)/
sqrt((f.ageTab$MOE_p^2) + (f.ageTab$MOE_c^2)))
f.ageTab$Sig_Diff <- ifelse(f.ageTab$ZScore < 1,"No","Yes")
f.ageTab$Difference <- ifelse(f.ageTab$Sig_Diff == "Yes", ifelse(f.ageTab$MedAge_p < f.ageTab$MedAge_c,"Younger","Older"),"")
m.ageTab <- as.matrix(f.ageTab[,c(1:5,7,8)])
}
#Column Names
if(nchar(placename) == 0) {
names_spaced <- c("Gender","Median Age","MOE","Median Age","MOE","Signficant Difference?","Difference from State")
} else {
names_spaced <- c("Gender","Median Age","MOE","Median Age","MOE","Signficant Difference?","Difference from County")
}
#Span Header
if(nchar(placefips) == 0) {
# create vector with colspan
tblHead <- c(" " = 1, ctyname = 2, "Colorado" = 2, " " = 2)
# set vector names
names(tblHead) <- c(" ", ctyname,"Colorado"," ")
} else {
# create vector with colspan
tblHead <- c(" " = 1, placename = 2, ctyname = 2, " " = 2)
# set vector names
names(tblHead) <- c(" ", placename,ctyname," ")
}
if(oType == "html") {
age_t <- m.ageTab %>%
kable(format='html', table.attr='class="cleanTable"',
digits=1,
row.names=FALSE,
align='lrrrrrr',
caption="Median Age by Gender Comparison",
col.names = names_spaced,
escape = FALSE) %>%
kable_styling(bootstrap_options = "condensed",full_width = F,font_size = 10) %>%
row_spec(0, align = "c") %>%
column_spec(1, width = "0.5in") %>%
column_spec(2, width = "0.75in") %>%
column_spec(3, width = "0.75in") %>%
column_spec(4, width = "0.75in") %>%
column_spec(5, width = "0.75in") %>%
column_spec(6, width = "1in") %>%
column_spec(7, width = "0.75in") %>%
add_header_above(header=tblHead) %>%
footnote(captionSrc("ACS",ACS))
# Building FlexTable
f.Flex <- as.data.frame(m.ageTab)
names(f.Flex) <- c("Gender","Age.1","MOE.1","Age.2","MOE.2","SD","Diff")
FlexOut <- regulartable(f.Flex)
FlexOut <- set_header_labels(FlexOut, Gender = "Gender",
Age.1 = "Estimate", MOE.1 = "Margin of Error",
Age.2 = "Estimate", MOE.2 = "Margin of Error",
SD="Signficant Difference?", Diff="Direction of Difference")
if(nchar(placefips) == 0) {
FlexOut <- add_header(FlexOut,Gender = "", Age.1= ctyname, MOE.1="",
Age.2 = "Colorado", MOE.2 = "",
SD = "", Diff = "",top=TRUE)
} else {
FlexOut <- add_header(FlexOut,Gender = "", Age.1 = placename, MOE.1 = "",
Age.2 = ctyname, MOE.2 ="",
SD = "", Diff = "",top=TRUE)
}
FlexOut <- add_header(FlexOut,Gender ="Median Age by Gender", top=TRUE)
FlexOut <- add_footer(FlexOut,Gender=captionSrc("ACS",ACS))
FlexOut <- merge_at(FlexOut,i=1,j = 1:7,part="header")
FlexOut <- merge_at(FlexOut,i=2,j = 2:3, part="header")
FlexOut <- merge_at(FlexOut,i=2,j = 4:5, part="header")
FlexOut <- merge_at(FlexOut,i=1, j = 1:7, part = "footer")
FlexOut <- align(FlexOut,i=1,j = 1, align="left",part="header")
FlexOut <- align(FlexOut,i=2:3,j = 1:7, align="center",part="header")
FlexOut <- align(FlexOut,i=1, align="left",part="footer")
FlexOut <- align(FlexOut, j=1, align="left", part="body")
FlexOut <- autofit(FlexOut)
FlexOut <- width(FlexOut, j = 1:5, width = 1)
#preparing Output data
f.ageTab2 <- f.ageTab[,c(1:5,7,8)]
if(nchar(placename) == 0) {
names(f.ageTab2) <- c("Gender", paste0("Median Age: ",ctyname), paste0("MOE: ",ctyname),
"Median Age: Colorado", "MOE: Colorado", "Sig. Difference","Difference from State")
} else {
names(f.ageTab2) <- c("Gender", paste0("Median Age: ",placename), paste0("MOE: ",placename),
paste0("Median Age: ",ctyname), paste0("MOE: ",ctyname), "Sig. Difference","Difference from County")
}
outList <- list("table" = age_t, "FlexTable" = FlexOut, "data" = f.ageTab2)
return(outList)
}
if(oType == "latex") {
tabOut <- m.ageTab %>% kable(digits=1,
row.names=FALSE,
col.names = names_spaced,
align='lrrrrrr',
caption="Median Age by Gender Comparison",
format="latex", booktabs=TRUE) %>%
kable_styling(latex_options="HOLD_position",font_size=10) %>%
row_spec(0, align="c") %>%
add_header_above(header=tblHead) %>%
footnote(captionSrc("ACS",ACS))
PlAge <- as.numeric(m.ageTab[3,2])
StAge <- as.numeric(m.ageTab[3,4])
dval <- ifelse(PlAge > StAge, PlAge - StAge,
ifelse(PlAge == StAge,0,StAge - PlAge))
sDiffa <- m.ageTab[3,6]
diffDira <- tolower(m.ageTab[3,7])
sDiffm <- m.ageTab[2,6]
diffDirm <- tolower(m.ageTab[2,7])
sDifff <- m.ageTab[1,6]
diffDirf <- tolower(m.ageTab[1,7])
if(nchar(placefips) == 0) {
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "Yes") {
medText <- paste0("The median age of ",ctyname," is ",round(dval,digits=1)," years ",diffDira," than the state.")
medText <- paste0(medText, " Women in ",ctyname," are significantly ",diffDirf, " than women in the state and men in ",ctyname," are significantly ",diffDirm," than men in the state.")
}
if(sDiffa == "Yes" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",ctyname," is ",round(dval,digits=1)," years ",diffDira," than the state.")
medText <- paste0(medText, " Women in ",ctyname," are significantly ", diffDirf," than women in the state but men are not sigificnatly older or younger than men in the state.")
}
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",ctyname," is ",round(dval,digits=1)," years ",diffDira," than the state.")
medText <- paste0(medText, " Women are not significantly older or younger than women in the state but men in ",ctyname," are significantly ",diffDirm," than men in the state.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",ctyname," is not significantly different from the state.")
medText <- paste0(medText, " Women in ",ctyname," are significantly ", diffDirf," than women in the state but men are not sigificnatly older or younger than men in the state.")
}
if(sDiffa == "No" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",ctyname," is not significantly different from the state.")
medText <- paste0(medText, " Women are not significantly older or younger than women in the state but men in ",ctyname," are significantly ",diffDirm," than men in the state.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "No") {
medText <- paste0("The median age of ",ctyname," is not significantly different than population of the state.")
}
} else {
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "Yes") {
medText <- paste0("The median age of ",placename," is ",round(dval,digits=1)," years ",diffDira," than ", ctyname,".")
medText <- paste0(medText, " Women in ",placename," are significantly ",diffDirf, " than women in ",ctyname," and men in ",placename," are significantly ",diffDirm," than men in ",ctyname,".")
}
if(sDiffa == "Yes" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",placename," is ",round(dval,digits=1)," years ",diffDira," than ", ctyname,".")
medText <- paste0(medText, " Women in ",placename," are significantly ", diffDirf," than women in ", ctyname," but men are not significantly older or younger than men in the county.")
}
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",placename," is ",round(dval,digits=1)," years ",diffDira," than the county.")
medText <- paste0(medText, " Women are not significantly older or younger than women in ", ctyname," but men in ",placename," are significantly ",diffDirm," than men in the county.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",placename," is nor significantly different than the population", ctyname,".")
medText <- paste0(medText, " Women in ",placename," are significantly ", diffDirf," than women in ", ctyname," but men are not significantly older or younger than men in the county.")
}
if(sDiffa == "No" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",placename," is nor significantly different than the population of ", ctyname,".")
medText <- paste0(medText, " Women are not significantly older or younger than women in ", ctyname," but men in ",placename," are significantly ",diffDirm," than men in the county.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "No") {
medText <- paste0(" The median age of ",placename," is not significantly different than the population of ",ctyname,".")
}
}
outList <- list("table" = tabOut, "text" = medText)
return(outList)
}
}
ColoradoDemography/codemogLib documentation built on Dec. 15, 2020, 2:42 a.m.
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Defines functions medianAgeTab
#' medianAgeTab Creates table showing the Median Age by Gender
#' for a selected place and county or for a copunty and for the state
#'
#' @param listID the list containing place id and Place names
#' @param ACS a string identifying the input dataset eg: "acs1115"
#' @param state the State FIPS code, defaluts to "08" for Colorado.
#' @param oType type of output, html or latex
#' @return a formatted table and dataset
#' @export
medianAgeTab <- function(listID, ACS, oType, state="08"){
# Collecting place ids from idList, setting default values
ctyfips <- listID$ctyNum
ctyname <- listID$ctyName
placefips <- listID$plNum
placename <- listID$plName
# if(listID$PlFilter == "T") {
# placefips <- ""
# placename <- ""
# }
#County Age
medAgecty <- codemog_api(data="b01002",db=ACS, geonum=paste("1", state, ctyfips, sep=""), meta="no")
medAgectyMOE <- codemog_api(data="b01002_moe",db=ACS, geonum=paste("1", state, ctyfips, sep=""), meta="no")
medAgecty2 <- gather(medAgecty[1,8:10])
medAgecty2$key <- c("Total","Male","Female")
names(medAgecty2)[2] <- "MedAge_c"
medAgecty2MOE <- gather(medAgectyMOE[1,8:10])
medAgecty2MOE$key <- c("Total","Male","Female")
names(medAgecty2MOE)[2] <- "MOE_c"
f.ctyAge <- merge(medAgecty2, medAgecty2MOE, by = "key")
#State Age
medAgeST <- codemog_api(data="b01002",db=ACS, geonum=paste("1", state, sep=""), meta="no")
medAgeSTMOE <- codemog_api(data="b01002_moe",db=ACS, geonum=paste("1", state, sep=""), meta="no")
medAgeST2 <- gather(medAgeST[1,8:10])
medAgeST2$key <- c("Total","Male","Female")
names(medAgeST2)[2] <- "MedAge_s"
medAgeST2MOE <- gather(medAgeSTMOE[1,8:10])
medAgeST2MOE$key <- c("Total","Male","Female")
names(medAgeST2MOE)[2] <- "MOE_s"
f.stateAge <- merge(medAgeST2, medAgeST2MOE, by = "key")
if(nchar(placefips) != 0) {
#place Age
medAgeplace <- codemog_api(data="b01002",db=ACS, geonum=paste("1", state, placefips, sep=""), meta="no")
medAgeplaceMOE <- codemog_api(data="b01002_moe",db=ACS, geonum=paste("1", state, placefips, sep=""), meta="no")
medAgeplace2 <- gather(medAgeplace[1,8:10])
medAgeplace2$key <- c("Total","Male","Female")
names(medAgeplace2)[2] <- "MedAge_p"
medAgeplace2MOE <- gather(medAgeplaceMOE[1,8:10])
medAgeplace2MOE$key <- c("Total","Male","Female")
names(medAgeplace2MOE)[2] <- "MOE_p"
f.placeAge <- merge(medAgeplace2, medAgeplace2MOE, by = "key")
}
#Creating Copmbined table and Calcualting tests
if(nchar(placefips) == 0) {
f.ageTab <- merge(f.ctyAge, f.stateAge, by = "key")
#Calculating significant differences
f.ageTab$MedAge_c <- as.numeric(f.ageTab$MedAge_c)
f.ageTab$MOE_c <- as.numeric(f.ageTab$MOE_c)
f.ageTab$MedAge_s <- as.numeric(f.ageTab$MedAge_s)
f.ageTab$MOE_s <- as.numeric(f.ageTab$MOE_s)
f.ageTab$ZScore <- (abs(f.ageTab$MedAge_c - f.ageTab$MedAge_s)/
sqrt((f.ageTab$MOE_c^2) + (f.ageTab$MOE_s^2)))
f.ageTab$Sig_Diff <- ifelse(f.ageTab$ZScore < 1,"No","Yes")
f.ageTab$Difference <- ifelse(f.ageTab$Sig_Diff == "Yes", ifelse(f.ageTab$MedAge_c < f.ageTab$MedAge_s,"Younger","Older"),"")
m.ageTab <- as.matrix(f.ageTab[,c(1:5,7,8)])
} else {
f.ageTab <- merge(f.placeAge, f.ctyAge, by = "key")
#Calculating significant differences
f.ageTab$MedAge_p <- as.numeric(f.ageTab$MedAge_p)
f.ageTab$MOE_p <- as.numeric(f.ageTab$MOE_p)
f.ageTab$MedAge_c <- as.numeric(f.ageTab$MedAge_c)
f.ageTab$MOE_c <- as.numeric(f.ageTab$MOE_c)
f.ageTab$ZScore <- (abs(f.ageTab$MedAge_p - f.ageTab$MedAge_c)/
sqrt((f.ageTab$MOE_p^2) + (f.ageTab$MOE_c^2)))
f.ageTab$Sig_Diff <- ifelse(f.ageTab$ZScore < 1,"No","Yes")
f.ageTab$Difference <- ifelse(f.ageTab$Sig_Diff == "Yes", ifelse(f.ageTab$MedAge_p < f.ageTab$MedAge_c,"Younger","Older"),"")
m.ageTab <- as.matrix(f.ageTab[,c(1:5,7,8)])
}
#Column Names
if(nchar(placename) == 0) {
names_spaced <- c("Gender","Median Age","MOE","Median Age","MOE","Signficant Difference?","Difference from State")
} else {
names_spaced <- c("Gender","Median Age","MOE","Median Age","MOE","Signficant Difference?","Difference from County")
}
#Span Header
if(nchar(placefips) == 0) {
# create vector with colspan
tblHead <- c(" " = 1, ctyname = 2, "Colorado" = 2, " " = 2)
# set vector names
names(tblHead) <- c(" ", ctyname,"Colorado"," ")
} else {
# create vector with colspan
tblHead <- c(" " = 1, placename = 2, ctyname = 2, " " = 2)
# set vector names
names(tblHead) <- c(" ", placename,ctyname," ")
}
if(oType == "html") {
age_t <- m.ageTab %>%
kable(format='html', table.attr='class="cleanTable"',
digits=1,
row.names=FALSE,
align='lrrrrrr',
caption="Median Age by Gender Comparison",
col.names = names_spaced,
escape = FALSE) %>%
kable_styling(bootstrap_options = "condensed",full_width = F,font_size = 10) %>%
row_spec(0, align = "c") %>%
column_spec(1, width = "0.5in") %>%
column_spec(2, width = "0.75in") %>%
column_spec(3, width = "0.75in") %>%
column_spec(4, width = "0.75in") %>%
column_spec(5, width = "0.75in") %>%
column_spec(6, width = "1in") %>%
column_spec(7, width = "0.75in") %>%
add_header_above(header=tblHead) %>%
footnote(captionSrc("ACS",ACS))
# Building FlexTable
f.Flex <- as.data.frame(m.ageTab)
names(f.Flex) <- c("Gender","Age.1","MOE.1","Age.2","MOE.2","SD","Diff")
FlexOut <- regulartable(f.Flex)
FlexOut <- set_header_labels(FlexOut, Gender = "Gender",
Age.1 = "Estimate", MOE.1 = "Margin of Error",
Age.2 = "Estimate", MOE.2 = "Margin of Error",
SD="Signficant Difference?", Diff="Direction of Difference")
if(nchar(placefips) == 0) {
FlexOut <- add_header(FlexOut,Gender = "", Age.1= ctyname, MOE.1="",
Age.2 = "Colorado", MOE.2 = "",
SD = "", Diff = "",top=TRUE)
} else {
FlexOut <- add_header(FlexOut,Gender = "", Age.1 = placename, MOE.1 = "",
Age.2 = ctyname, MOE.2 ="",
SD = "", Diff = "",top=TRUE)
}
FlexOut <- add_header(FlexOut,Gender ="Median Age by Gender", top=TRUE)
FlexOut <- add_footer(FlexOut,Gender=captionSrc("ACS",ACS))
FlexOut <- merge_at(FlexOut,i=1,j = 1:7,part="header")
FlexOut <- merge_at(FlexOut,i=2,j = 2:3, part="header")
FlexOut <- merge_at(FlexOut,i=2,j = 4:5, part="header")
FlexOut <- merge_at(FlexOut,i=1, j = 1:7, part = "footer")
FlexOut <- align(FlexOut,i=1,j = 1, align="left",part="header")
FlexOut <- align(FlexOut,i=2:3,j = 1:7, align="center",part="header")
FlexOut <- align(FlexOut,i=1, align="left",part="footer")
FlexOut <- align(FlexOut, j=1, align="left", part="body")
FlexOut <- autofit(FlexOut)
FlexOut <- width(FlexOut, j = 1:5, width = 1)
#preparing Output data
f.ageTab2 <- f.ageTab[,c(1:5,7,8)]
if(nchar(placename) == 0) {
names(f.ageTab2) <- c("Gender", paste0("Median Age: ",ctyname), paste0("MOE: ",ctyname),
"Median Age: Colorado", "MOE: Colorado", "Sig. Difference","Difference from State")
} else {
names(f.ageTab2) <- c("Gender", paste0("Median Age: ",placename), paste0("MOE: ",placename),
paste0("Median Age: ",ctyname), paste0("MOE: ",ctyname), "Sig. Difference","Difference from County")
}
outList <- list("table" = age_t, "FlexTable" = FlexOut, "data" = f.ageTab2)
return(outList)
}
if(oType == "latex") {
tabOut <- m.ageTab %>% kable(digits=1,
row.names=FALSE,
col.names = names_spaced,
align='lrrrrrr',
caption="Median Age by Gender Comparison",
format="latex", booktabs=TRUE) %>%
kable_styling(latex_options="HOLD_position",font_size=10) %>%
row_spec(0, align="c") %>%
add_header_above(header=tblHead) %>%
footnote(captionSrc("ACS",ACS))
PlAge <- as.numeric(m.ageTab[3,2])
StAge <- as.numeric(m.ageTab[3,4])
dval <- ifelse(PlAge > StAge, PlAge - StAge,
ifelse(PlAge == StAge,0,StAge - PlAge))
sDiffa <- m.ageTab[3,6]
diffDira <- tolower(m.ageTab[3,7])
sDiffm <- m.ageTab[2,6]
diffDirm <- tolower(m.ageTab[2,7])
sDifff <- m.ageTab[1,6]
diffDirf <- tolower(m.ageTab[1,7])
if(nchar(placefips) == 0) {
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "Yes") {
medText <- paste0("The median age of ",ctyname," is ",round(dval,digits=1)," years ",diffDira," than the state.")
medText <- paste0(medText, " Women in ",ctyname," are significantly ",diffDirf, " than women in the state and men in ",ctyname," are significantly ",diffDirm," than men in the state.")
}
if(sDiffa == "Yes" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",ctyname," is ",round(dval,digits=1)," years ",diffDira," than the state.")
medText <- paste0(medText, " Women in ",ctyname," are significantly ", diffDirf," than women in the state but men are not sigificnatly older or younger than men in the state.")
}
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",ctyname," is ",round(dval,digits=1)," years ",diffDira," than the state.")
medText <- paste0(medText, " Women are not significantly older or younger than women in the state but men in ",ctyname," are significantly ",diffDirm," than men in the state.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",ctyname," is not significantly different from the state.")
medText <- paste0(medText, " Women in ",ctyname," are significantly ", diffDirf," than women in the state but men are not sigificnatly older or younger than men in the state.")
}
if(sDiffa == "No" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",ctyname," is not significantly different from the state.")
medText <- paste0(medText, " Women are not significantly older or younger than women in the state but men in ",ctyname," are significantly ",diffDirm," than men in the state.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "No") {
medText <- paste0("The median age of ",ctyname," is not significantly different than population of the state.")
}
} else {
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "Yes") {
medText <- paste0("The median age of ",placename," is ",round(dval,digits=1)," years ",diffDira," than ", ctyname,".")
medText <- paste0(medText, " Women in ",placename," are significantly ",diffDirf, " than women in ",ctyname," and men in ",placename," are significantly ",diffDirm," than men in ",ctyname,".")
}
if(sDiffa == "Yes" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",placename," is ",round(dval,digits=1)," years ",diffDira," than ", ctyname,".")
medText <- paste0(medText, " Women in ",placename," are significantly ", diffDirf," than women in ", ctyname," but men are not significantly older or younger than men in the county.")
}
if(sDiffa == "Yes" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",placename," is ",round(dval,digits=1)," years ",diffDira," than the county.")
medText <- paste0(medText, " Women are not significantly older or younger than women in ", ctyname," but men in ",placename," are significantly ",diffDirm," than men in the county.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "Yes") {
medText <- paste0("The median age of ",placename," is nor significantly different than the population", ctyname,".")
medText <- paste0(medText, " Women in ",placename," are significantly ", diffDirf," than women in ", ctyname," but men are not significantly older or younger than men in the county.")
}
if(sDiffa == "No" & sDiffm == "Yes" && sDifff == "No") {
medText <- paste0("The median age of ",placename," is nor significantly different than the population of ", ctyname,".")
medText <- paste0(medText, " Women are not significantly older or younger than women in ", ctyname," but men in ",placename," are significantly ",diffDirm," than men in the county.")
}
if(sDiffa == "No" & sDiffm == "No" && sDifff == "No") {
medText <- paste0(" The median age of ",placename," is not significantly different than the population of ",ctyname,".")
}
}
outList <- list("table" = tabOut, "text" = medText)
return(outList)
}
}
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