Fixed fig 3D, import of female data twice instead of female/male data

Code/.Rhistory

@@ -0,0 +1,158 @@
+library(ggplot2)
+library(readr)
+library(dplyr)
+library(scales)
+library(readxl)
+library(cowplot)
+library(readxl)
+Early_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageEarly.xlsx") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value", "Rate" = "Observed Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model), Rate = as.numeric(Rate), AgeCategory = "Early")
+Middle_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageMiddle.xlsx") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value", "Rate" = "Observed Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model), Rate = as.numeric(Rate), AgeCategory = "Middle")
+Late_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageLate.xlsx") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value", "Rate" = "Observed Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model), Rate = as.numeric(Rate), AgeCategory = "Late")
+AllAges_JP <- rbind(Early_JP, Middle_JP, Late_JP)
+AllAges_JP$AgeCategory <- factor(AllAges_JP$AgeCategory, levels = c("Early","Middle","Late"))
+colorclasses <- c("Localized" = "#016b0b","Distant" = "#be0306","Regional" = "#ffb401")
+shapes <- c(8, 15, 17)
+lwds <- c(3, 4, 2, 1)
+Figure2A <- ggplot() +
+geom_point(data=AllAges_JP, aes(x=Year, y=Rate, col=Stage, group=Stage, shape=Stage), size=2) +
+geom_line(data = AllAges_JP, aes(x=Year, y=Model, group=Stage, col=Stage)) +
+facet_wrap( ~ AgeCategory, scales = "free_y") +
+scale_x_continuous(breaks=c(1998, 2000, 2005, 2010, 2014), labels = c("1998", "2000", "2005", "2010", "2014"), minor_breaks = seq(1998,2014,1)) +
+ylab("Incidence rate (per 100,000)")
+Figure2A_themed <- Figure2A +
+scale_color_manual(name="Stage",values = colorclasses) +
+scale_shape_manual(values=shapes) +
+theme_classic() +
+theme(
+legend.position = "none",
+axis.title = element_text(size = 12, face="bold"),
+axis.text = element_text(size=10),
+axis.text.x = element_text(angle=45, vjust=0.5)
+)
+Figure2A_themed
+Prox_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageProximal.xlsx") %>% rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Side = "Proximal")
+Dist_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageDistal.xlsx") %>% rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Side = "Distal")
+AllSides_JP <- rbind(Prox_JP, Dist_JP)
+AllSides_JP$Side <- factor(AllSides_JP$Side, levels=c("Proximal","Distal"))
+AllSides_JP$Stage <- factor(AllSides_JP$Stage, levels = c("Localized","Regional","Distant"))
+colorclasses <- c("Localized" = "#016b0b", "Distant" = "#be0306", "Regional" = "#ffb401")
+shapes <- c(15, 17, 8)
+lwds <- c(3, 4, 2, 1)
+Figure2B <- ggplot(AllSides_JP) +
+geom_point(aes(x=Year, y=Rate, col=Stage, group=Stage, shape=Stage), size=2) +
+geom_line(aes(x=Year, y=Model, col=Stage, group=Stage)) +
+facet_wrap(~ Side) +
+scale_x_continuous(breaks=c(1998, 2000, 2005, 2010, 2014), labels = c("1998", "2000", "2005", "2010", "2014"), minor_breaks = seq(1998,2014,1)) +
+ylab("Incidence rate (per 100,000)")
+Figure2B_themed <- Figure2B +
+scale_color_manual(name="Stage",values = colorclasses) +
+scale_shape_manual(values=shapes) +
+theme_classic() +
+theme(
+legend.position = "none",
+axis.title = element_text(size = 12, face="bold"),
+axis.text = element_text(size=10),
+axis.text.x = element_text(angle=45, vjust=0.5)
+)
+Figure2B_themed
+#ggsave(plot=Figure2B_themed, filename="Figure2B.tiff", path="C:/Users/gaugustus/Documents/Success_Docs/Pubs/DistantCRC_BriefComm", device = "tiff", width=16, height=10, units="cm", dpi = 300)
+CRCSites <- readr::read_delim("K:/SEER_DataTables/SEER_2000-2014_CRC_StageDistribution_Race.txt", "\t", escape_double = FALSE, trim_ws = TRUE)
+colnames(CRCSites) <- c("Year","Race", "Stage","Rate", "Count", "Population")
+CRCSites2 <- CRCSites %>% filter(!grepl("-", Year)) %>% filter(Stage %in% c("Distant","Localized","Regional","Unknown/unstaged")) %>% filter(Year >= 1998) %>% filter(! Race %in% c("Unknown"))
+CRCSites2$Year <- as.integer(CRCSites2$Year)
+CRCSites2$Stage <- factor(CRCSites2$Stage, levels=c("Unknown/unstaged","Localized","Regional","Distant"))
+CRCSites2$Race <- factor(CRCSites2$Race, levels=c("Black", "American Indian/Alaska Native","Asian or Pacific Islander","White"), labels = c("Black or African American", "American Indian/Alaska Native","Asian or Pacific Islander","White"))
+CRCSites2
+library(readxl)
+AI_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageAmericanIndian.xlsx", sheet=3) %>% mutate(Race = "American Indian/Alaska Native") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model), APC=NULL)
+A_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageAsian.xlsx", sheet=3) %>% mutate(Race = "Asian or Pacific Islander") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model))
+B_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageBlack.xlsx", sheet=1) %>% mutate(Race = "Black or African American") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model))
+W_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageWhite.xlsx", sheet=1) %>% mutate(Race = "White") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model))
+AllRace_JPs <- rbind(AI_JPs, A_JPs, B_JPs, W_JPs)
+AllRace_JPs <- rbind(AI_JPs, A_JPs, B_JPs, W_JPs)
+dim(AI_JPs)
+dim(A_JPs)
+dim(B_JPs)
+dim(W_JPs)
+colnames(W_JPs)
+head(W_JPs)
+colnames(B_JPs)
+View(W_JPs)
+W_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageWhite.xlsx", sheet=1) %>%
+mutate(Race = "White") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>%
+mutate(Year = as.integer(Year), Model = as.numeric(Model), X__1=NULL, X__2=NULL)
+AllRace_JPs <- rbind(AI_JPs, A_JPs, B_JPs, W_JPs)
+colorclasses <- c("Localized" = "#016b0b","Distant" = "#be0306","Regional" = "#ffb401")
+shapes <- c(15,  17, 8)
+lwds <- c(3, 2, 1)
+Races <- list(
+'Black or African American'="Black or\nAfrican American",
+'American Indian/Alaska Native'="Native American\nAlaska Native",
+'Asian or Pacific Islander'="Asian or\nPacific Islander",
+'White' = "White"
+)
+Races_labeller <- function(variable,value){
+return(Races[value])
+}
+Figure2C <- ggplot() +
+geom_point(data=CRCSites2 %>% filter(Stage != "Unknown/unstaged"), aes(x=Year, y=Rate, col=Stage, group=Stage, shape=Stage), size=2) +
+geom_line(data=AllRace_JPs, aes(x=Year, y=Model, group=Stage, col=Stage)) +
+facet_grid(. ~ Race, labeller = Races_labeller) +
+scale_x_continuous(breaks=c(1998, 2000, 2005, 2010, 2014), labels = c("1998", "2000", "2005", "2010", "2014"), minor_breaks = seq(1998,2014,1)) +
+scale_y_continuous() +
+ylab("Incidence rate (per 100,000)") +
+ggtitle(" ")
+Figure2C_themed <- Figure2C +
+scale_color_manual(name="Stage", values = colorclasses) +
+scale_shape_manual(values=shapes) +
+theme_classic() +
+theme(
+legend.position = "none",
+axis.title = element_text(size = 12, face="bold"),
+axis.text = element_text(size=10),
+axis.text.x = element_text(angle=45, vjust=0.5)
+)
+Figure2C_themed
+#ggsave(plot=Figure2C_themed, filename="Figure2C.tiff", path="C:/Users/gaugustus/Documents/Success_Docs/Pubs/DistantCRC_BriefComm/", device = "tiff", width=16, height=10, units="cm", dpi = 300)
+RateFemale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageFemale.xlsx") %>% rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Female")
+RateMale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageFemale.xlsx") %>% rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Male")
+AllSex_JP <- rbind(RateFemale_JP, RateMale_JP)
+RateFemale_JP == RateMale_JP
+RateFemale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageFemale.xlsx") %>%
+rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>%
+mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Female")
+RateMale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageMale.xlsx") %>%
+rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>%
+mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Male")
+AllSex_JP <- rbind(RateFemale_JP, RateMale_JP)
+colorclasses <- c("Localized" = "#016b0b", "Distant" = "#be0306", "Regional" = "#ffb401")
+shapes <- c(8, 15, 17)
+lwds <- c(3, 4, 2, 1)
+Figure2D <- ggplot(AllSex_JP) +
+geom_point(aes(x=Year, y=Rate, col=Stage, group=Stage, shape=Stage), size=2) +
+geom_line(aes(x=Year, y=Model, col=Stage, group=Stage)) +
+facet_wrap(~ Sex) +
+scale_x_continuous(breaks=c(1998, 2000, 2005, 2010, 2014), labels = c("1998", "2000", "2005", "2010", "2014"), minor_breaks = seq(1998,2014,1)) +
+ylab("Incidence rate (per 100,000)")
+Figure2D_themed <- Figure2D +
+scale_color_manual(name="Stage",values = colorclasses) +
+scale_shape_manual(values=shapes) +
+theme_classic() +
+theme(
+legend.position = "none",
+axis.title = element_text(size = 12, face="bold"),
+axis.text = element_text(size=10),
+axis.text.x = element_text(angle=45, vjust=0.5)
+)
+Figure2D_themed
+Legend <- get_legend(Figure2B_themed + theme(legend.position = "bottom",
+legend.title = element_text(size=12, face="bold"),
+legend.text = element_text(size=10)))
+prow <- plot_grid(Figure2A_themed, Figure2B_themed, Figure2C_themed, Figure2D_themed, labels = c("A", "B", "C", "D"), hjust = -1, nrow = 2, align = "vh", label_size = 26)
+p <- plot_grid(prow, Legend, ncol=1, rel_heights = c(1, .1))
+p
+#ggsave(plot=p, filename="Figure2.tiff", path="C:/Users/gaugustus/Documents/Success_Docs/Pubs/DistantCRC_BriefComm", device = "tiff", width=33, height=20, units="cm", dpi = 300)
+#ggsave(plot=p, filename="Figure2_Proof.tiff", path="C:/Users/gaugustus/Documents/Success_Docs/Pubs/DistantCRC_BriefComm", device = "tiff", width=33, height=20, units="cm", dpi = 72)
+ggsave(plot=p, filename="Figure3_1200px.tiff", path="U:/Box Sync/Distant CRC - JNCI Brief Comm", device = "tiff", width=12, height=7.5, units = "in", dpi=100)
+ggsave(plot=p, filename="Figure3.tiff", path="U:/Box Sync/Distant CRC - JNCI Brief Comm", device = "tiff", width=12, height=7.5, units = "in", dpi=300)
+sessionInfo()

Code/DistantCRC_Figures_Fig3_cowplot.Rmd

@@ -143,10 +143,21 @@ library(readxl)
 ```
 
 ```{r}
-AI_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageAmericanIndian.xlsx", sheet=3) %>% mutate(Race = "American Indian/Alaska Native") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model), APC=NULL)
-A_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageAsian.xlsx", sheet=3) %>% mutate(Race = "Asian or Pacific Islander") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model))
-B_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageBlack.xlsx", sheet=1) %>% mutate(Race = "Black or African American") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model))
-W_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageWhite.xlsx", sheet=1) %>% mutate(Race = "White") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Model = as.numeric(Model))
+AI_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageAmericanIndian.xlsx", sheet=3) %>% 
+     mutate(Race = "American Indian/Alaska Native") %>% 
+     rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% 
+     mutate(Year = as.integer(Year), Model = as.numeric(Model), APC=NULL)
+A_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageAsian.xlsx", sheet=3) %>% 
+     mutate(Race = "Asian or Pacific Islander") %>% 
+     rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% 
+     mutate(Year = as.integer(Year), Model = as.numeric(Model))
+B_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageBlack.xlsx", sheet=1) %>% 
+     mutate(Race = "Black or African American") %>% 
+     rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% 
+     mutate(Year = as.integer(Year), Model = as.numeric(Model))
+W_JPs <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageWhite.xlsx", sheet=1) %>% 
+     mutate(Race = "White") %>% rename("Year" = "X Value", "Model" = "Modeleded Y Value") %>% 
+     mutate(Year = as.integer(Year), Model = as.numeric(Model), X__1=NULL, X__2=NULL)
 
 AllRace_JPs <- rbind(AI_JPs, A_JPs, B_JPs, W_JPs)
 ```
@@ -205,8 +216,12 @@ Figure2C_themed
 
 # D: Sex
 ```{r}
-RateFemale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageFemale.xlsx") %>% rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Female")
-RateMale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageFemale.xlsx") %>% rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Male")
+RateFemale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageFemale.xlsx") %>% 
+     rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% 
+     mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Female")
+RateMale_JP <- read_excel("U:/Box Sync/ProjectDocs/2017_DistantCRC/JoinPoint/Rate_StageMale.xlsx") %>% 
+     rename("Year" = "X Value", "Rate" = "Observed Y Value", "Model" = "Modeleded Y Value") %>% 
+     mutate(Year = as.integer(Year), Rate = as.numeric(Rate), Model = as.numeric(Model), Sex = "Male")
 
 AllSex_JP <- rbind(RateFemale_JP, RateMale_JP)