Register variables as numeric for analysis

jnumeric() tells jstats to treat one or more variables as numeric (continuous) wherever their analysis class matters, overriding the package's automatic structural guess. It is the counterpart to jdummy (categorical) and jcount (count): a variable carries exactly one registered intent at a time, so registering it as numeric clears any prior dummy or count registration. Registration changes no data and assigns nothing – you do not write df <- jnumeric(...). It is stored for the session, keyed by the data frame's name; save the data frame in R format (.rds) to keep it across sessions.

Usage

jnumeric(data, ..., remove = FALSE, clear.all = FALSE)

Arguments

data: A data frame, or omitted to use the juse default. jnumeric(NULL) clears the numeric registrations on the juse default frame (or, with no default set, the only frame that carries them; if several do, it asks rather than wiping all). jnumeric(data, NULL) clears that one frame's numeric registrations. Called with no arguments, jnumeric() lists the session's numeric and count registrations.
...: One or more unquoted variable names to register.
remove: Logical; if TRUE, remove the numeric registration for the named variables instead of adding it.
clear.all: Logical; if TRUE, clear numeric registrations on every data frame that carries them.

Value

invisible(NULL). Called for its side effect on the session registration notebook.

Details

The typical use is a small-range whole number that the structural classifier would treat as categorical (e.g. a 0-6 attitude item) but that you want analyzed as a continuous score.

Examples

# Treat a labelled Likert item as a continuous score (slope-per-unit)
jnumeric(community, Environment2)             # one labelled 1-5 item
#> Numeric registration set for 'Environment2' in community.
#> Note: this registration is stored for this session only.
#> To keep it across sessions, save the data frame in R format (.rds):
#>   jsave(community, "community.rds")
#> 
#> Next session, load that file to restore the registration:
#>   community <- jload("community.rds")
jnumeric(community, Environment2, Environment4)  # several at once
#> Numeric registration set for 'Environment2', 'Environment4' in community.
#> Note: registrations are stored for this session only.
#> To keep them across sessions, save the data frame in R format (.rds):
#>   jsave(community, "community.rds")
#> 
#> Next session, load that file to restore the registrations:
#>   community <- jload("community.rds")
jnumeric(community, Environment2, remove = TRUE) # unregister one
#> Numeric registration removed for 'Environment2' in community.
jnumeric()                          # list all registrations
#> Variable Registrations
#> Data frame: community
#> 
#>   Environment4: numeric
#> 
jnumeric(community, NULL)           # clear community's numeric registrations
#> Numeric registrations cleared for community: Environment4.
jnumeric(clear.all = TRUE)          # clear every frame's numeric registrations
#> No numeric registrations to clear.