Nothing
## ----echo=FALSE---------------------------------------------------------------
knitr::opts_chunk$set(comment = "#")
## ----message=FALSE------------------------------------------------------------
library(rtables)
library(dplyr)
## ----echo=FALSE, fig.align='center'-------------------------------------------
knitr::include_graphics("./images/rtables-basics.png")
## ----data---------------------------------------------------------------------
n <- 400
set.seed(1)
df <- tibble(
arm = factor(sample(c("Arm A", "Arm B"), n, replace = TRUE), levels = c("Arm A", "Arm B")),
country = factor(sample(c("CAN", "USA"), n, replace = TRUE, prob = c(.55, .45)), levels = c("CAN", "USA")),
gender = factor(sample(c("Female", "Male"), n, replace = TRUE), levels = c("Female", "Male")),
handed = factor(sample(c("Left", "Right"), n, prob = c(.6, .4), replace = TRUE), levels = c("Left", "Right")),
age = rchisq(n, 30) + 10
) %>% mutate(
weight = 35 * rnorm(n, sd = .5) + ifelse(gender == "Female", 140, 180)
)
head(df)
## ----echo=FALSE---------------------------------------------------------------
lyt <- basic_table(show_colcounts = TRUE) %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
split_rows_by("country") %>%
summarize_row_groups() %>%
split_rows_by("handed") %>%
summarize_row_groups() %>%
analyze("age", afun = mean, format = "xx.xx")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
qtable(df,
row_vars = c("country", "handed"),
col_vars = c("arm", "gender"),
avar = "age",
afun = mean,
summarize_groups = TRUE,
row_labels = "mean"
)
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
analyze("age", mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
lyt
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
split_rows_by("country") %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
mean(df$age[df$country == "CAN" & df$arm == "Arm A" & df$gender == "Female"])
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
split_rows_by("country", page_by = TRUE) %>%
split_rows_by("handed") %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
cat(export_as_txt(tbl, page_type = "letter", page_break = "\n\n~~~~~~ Page Break ~~~~~~\n\n"))
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
split_rows_by("country") %>%
summarize_row_groups() %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
df_cell <- subset(df, df$country == "CAN" & df$arm == "Arm A" & df$gender == "Female")
df_col_1 <- subset(df, df$arm == "Arm A" & df$gender == "Female")
c(count = nrow(df_cell), percentage = nrow(df_cell) / nrow(df_col_1))
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
split_rows_by("country") %>%
summarize_row_groups() %>%
split_rows_by("handed") %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
## -----------------------------------------------------------------------------
lyt <- basic_table() %>%
split_cols_by("arm") %>%
split_cols_by("gender") %>%
split_rows_by("country") %>%
summarize_row_groups() %>%
split_rows_by("handed") %>%
summarize_row_groups() %>%
analyze("age", afun = mean, format = "xx.x")
tbl <- build_table(lyt, df)
tbl
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