Set labels in the function call

The summary() method for tableby(), modelsum(), and freqlist() objects contains a labelTranslations = argument to specify labels in the function call. Note that the freqlist() function matches labels in order, whereas the other two match labels by name. The labels can be input as a list or a character vector.

summary(freqlist(tab.ex),
        labelTranslations = c(arm = "Treatment Arm", sex = "Gender", mdquality.s = "LASA QOL"))

summary(tableby(arm ~ sex + age, data = mockstudy),
        labelTranslations = c(sex = "SEX", age = "Age, yrs"))

summary(modelsum(bmi ~ age, adjust = ~sex, data = mockstudy),
        labelTranslations = list(sexFemale = "Female", age = "Age, yrs"))

Modify labels after the fact

Another option is to add labels after you have created the object. To do this, you can use the form labels(x) <- value or use the pipe-able version, set_labels().

# the non-pipe version; somewhat clunky
tmp <- freqlist(tab.ex)
labels(tmp) <- c(arm = "Treatment Arm", sex = "Gender", mdquality.s = "LASA QOL")
summary(tmp)

# piped--much cleaner
mockstudy %>% 
  tableby(arm ~ sex + age, data = .) %>% 
  set_labels(c(sex = "SEX", age = "Age, yrs")) %>% 
  summary()

mockstudy %>% 
  modelsum(bmi ~ age, adjust = ~ sex, data = .) %>% 
  set_labels(list(sexFemale = "Female", age = "Age, yrs")) %>% 
  summary()

Add labels to a data.frame

tableby() and modelsum() also allow you to have label attributes on the data. Note that by default these attributes usually get dropped upon subsetting, but tableby() and modelsum() use the keep.labels() function to retain them.

mockstudy.lab <- keep.labels(mockstudy)
class(mockstudy$age)

[1] “integer”

class(mockstudy.lab$age)

[1] “keep_labels” “integer”

To undo this, simply loosen.labels():

class(loosen.labels(mockstudy.lab)$age)

[1] “integer”

You can set attributes one at a time in two ways:

attr(mockstudy.lab$sex, "label") <- "Sex"
labels(mockstudy.lab$age) <- "Age, yrs"

…or all at once:

labels(mockstudy.lab) <- list(sex = "Sex", age = "Age, yrs")
summary(tableby(arm ~ sex + age, data = mockstudy.lab))

You can pipe this, too.

mockstudy %>% 
  set_labels(list(sex = "SEX", age = "Age, yrs")) %>% 
  modelsum(bmi ~ age, adjust = ~ sex, data = .) %>% 
  summary()

To extract labels from a data.frame, simply use the labels() function:

labels(mockstudy.lab)

## $case
## NULL
## 
## $age
## [1] "Age, yrs"
## 
## $arm
## [1] "Treatment Arm"
## 
## $sex
## [1] "Sex"
## 
## $race
## [1] "Race"
## 
## $fu.time
## NULL
## 
## $fu.stat
## NULL
## 
## $ps
## NULL
## 
## $hgb
## NULL
## 
## $bmi
## [1] "Body Mass Index (kg/m^2)"
## 
## $alk.phos
## NULL
## 
## $ast
## NULL
## 
## $mdquality.s
## NULL
## 
## $age.ord
## NULL

When labels get long

tableby() and modelsum() both support the wrapping of long labels. Consider the width= argument in the print() function:

mockstudy %>% 
  set_labels(list(age = "This is a really long label for the arm variable")) %>% 
  tableby(sex ~ age, data = .) %>% 
  summary() %>% 
  print(width = 20)