## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", results = "hold", collapse = TRUE, eval = TRUE, fig.pos = 'h', fig.align = 'center' ) ## ----message=FALSE, warning=FALSE, eval=T------------------------------------- library(surveil) library(ggplot2) library(knitr) ## ----eval=T------------------------------------------------------------------- head(msa) |> kable(booktabs = TRUE, caption = "Glimpse of colorectal cancer incidence data (CDC Wonder)") ## ----message = FALSE, warn = FALSE, eval = T---------------------------------- msa2 <- aggregate(cbind(Count, Population) ~ Year + Race, data = msa, FUN = sum) ## ----eval = T----------------------------------------------------------------- head(msa2) |> kable(booktabs = TRUE, caption = "Glimpse of aggregated Texas metropolitan CRC cases, by race and year") ## ----------------------------------------------------------------------------- fit <- stan_rw(msa2, time = Year, group = Race, iter = 1e3) ## ----------------------------------------------------------------------------- print(fit, scale = 100e3) ## ----------------------------------------------------------------------------- head(fit$summary) ## ----fig.width = 4.75, fig.height = 3.5--------------------------------------- plot(fit, scale = 100e3) ## ----fig.width = 7, fig.height = 3.5------------------------------------------ fig <- plot(fit, scale = 100e3, base_size = 11, size = 0) fig + theme(legend.position = "right") + labs(title = "CRC incidence per 100,000", subtitle = "Texas MSAs, 50-79 y.o.") ## ----fig.width = 4.5, fig.height = 3.5---------------------------------------- plot(fit, scale = 100e3, base_size = 11, style = "lines") ## ----------------------------------------------------------------------------- fit_pc <- apc(fit) ## ----------------------------------------------------------------------------- head(fit_pc$apc) ## ----------------------------------------------------------------------------- head(fit_pc$cpc) ## ----fig.width = 7, fig.height = 3.5------------------------------------------ plot(fit_pc, cumulative = TRUE) ## ----eval = FALSE------------------------------------------------------------- # fit <- stan_rw(msa2, time = Year, group = Race, cor = TRUE)