descfreq | R Documentation |
Create a summary table for one or more variables by one group, as well as a total column if necessary.
descfreq(
data,
denom = NULL,
var,
bygroup,
format,
fctdrop = FALSE,
addtot = FALSE,
na_str = NULL
)
data |
( |
denom |
( |
var |
( |
bygroup |
( |
format |
( |
fctdrop |
( |
addtot |
( |
na_str |
( |
A object Desc
contains an intermediate data with long form for
post-processing and final data with wide form for presentation.
By default, the each category is sorted based on the corresponding factor
level of var
variable. If the variable is not a factor, that will be sorted
alphabetically.
data(adsl_sub)
# Count the age group by treatment with 'xx (xx.x%)' format
adsl_sub %>%
descfreq(
var = "AGEGR1",
bygroup = "TRTP",
format = "xx (xx.x%)"
)
# Count the race by treatment with 'xx (xx.xx)' format and replace NA with '0'
adsl_sub %>%
descfreq(
var = "RACE",
bygroup = "TRTP",
format = "xx (xx.xx)",
na_str = "0"
)
# Count the sex by treatment adding total column
adsl_sub %>%
descfreq(
var = "SEX",
bygroup = "TRTP",
format = "xx (xx.x%)",
addtot = TRUE
)
# Count multiple variables by treatment and sort category by corresponding factor levels
adsl_sub %>%
dplyr::mutate(
AGEGR1 = factor(AGEGR1, levels = c("<65", "65-80", ">80")),
SEX = factor(SEX, levels = c("M", "F")),
RACE = factor(RACE, levels = c(
"WHITE", "AMERICAN INDIAN OR ALASKA NATIVE",
"BLACK OR AFRICAN AMERICAN"
))
) %>%
descfreq(
var = c("AGEGR1", "SEX", "RACE"),
bygroup = "TRTP",
format = "xx (xx.x%)",
addtot = TRUE,
na_str = "0"
)
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