sjmisc (version 2.7.7)

ref_lvl: Change reference level of (numeric) factors

Description

Changes the reference level of (numeric) factor.

Usage

ref_lvl(x, ..., lvl = NULL)

Arguments

x

A vector or data frame.

...

Optional, unquoted names of variables that should be selected for further processing. Required, if x is a data frame (and no vector) and only selected variables from x should be processed. You may also use functions like : or tidyselect's select_helpers. See 'Examples' or package-vignette.

lvl

Eiher numeric, indicating the new reference level, or a string, indicating the value label from the new reference level. If x is a factor with non-numeric factor levels, relevel(x, ref = lvl) is returned. See 'Examples'.

Value

x with new reference level. If x is a data frame, the complete data frame x will be returned, where variables specified in ... will be re-leveled; if ... is not specified, applies to all variables in the data frame.

Details

Unlike relevel, this function behaves differently for factor with numeric factor levels or for labelled data, i.e. factors with value labels for the values. ref_lvl() changes the reference level by recoding the factor's values using the rec function. Hence, all values from lowest up to the reference level indicated by lvl are recoded, with lvl starting as lowest factor value. For factors with non-numeric factor levels, the function simply returns relevel(x, ref = lvl). See 'Examples'.

See Also

to_factor to convert numeric vectors into factors; rec to recode variables.

Examples

# NOT RUN {
data(efc)
x <- to_factor(efc$e42dep)
str(x)
frq(x)

# see column "val" in frq()-output, which indicates
# how values/labels were recoded after using ref_lvl()
x <- ref_lvl(x, lvl = 3)
str(x)
frq(x)

library(dplyr)
dat <- efc %>%
  select(c82cop1, c83cop2, c84cop3) %>%
  to_factor()

frq(dat)
ref_lvl(dat, c82cop1, c83cop2, lvl = 2) %>% frq()

# compare numeric and string value for "lvl"-argument
x <- to_factor(efc$e42dep)
frq(x)
ref_lvl(x, lvl = 2) %>% frq()
ref_lvl(x, lvl = "slightly dependent") %>% frq()

# factors with non-numeric factor levels
data(iris)
levels(iris$Species)
levels(ref_lvl(iris$Species, lvl = 3))
levels(ref_lvl(iris$Species, lvl = "versicolor"))

# }