Register variables as Likert (ordered response) items

jlikert() declares one or more value-labelled variables as Likert items – ordered response scales (for example 1 = Strongly disagree through 5 = Strongly agree). It is the ordered-scale counterpart to jdummy (categorical), jnumeric (continuous), and jcount (count): a variable carries exactly one registered intent at a time, so registering it as Likert clears any prior numeric, count, or dummy registration on it.

Usage

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

Arguments

data: A data frame, or omitted to use the juse default.
...: One or more unquoted variable names to register, or a single NULL to clear this frame's Likert registrations (see Details).
remove: Logical; if TRUE, remove the named variables' Likert registrations instead of adding them.
clear.all: Logical; if TRUE, clear Likert registrations on every data frame.

Value

Invisibly NULL. Called for its side effect on the session registry.

Details

Scope – display only. The Likert intent refines reporting, not analysis. It sets the variable's sub-class to "Likert" in jscreen's Variable Types table, marking it as an ordered scale rather than a generic N-category variable. It does NOT change how any analysis treats the variable (there is no order-aware modelling), and it does not by itself change jplot output – a value-labelled small-range variable already plots as an ordered, labelled bar regardless of this registration.

Like the other registration verbs, registrations are session-scoped and keyed by data-frame name; save the frame in R format (.rds) with jsave to keep them across sessions.

Clearing mirrors the other registration verbs:

jlikert(data, NULL) – clear this frame's Likert registrations.
jlikert(NULL) – clear the juse() default frame (or the sole frame carrying Likert registrations; if several do, it asks rather than clearing them all).
jlikert(clear.all = TRUE) – clear every frame.

jlikert() with no arguments prints the current registration status.

Examples

  jlikert(community, Environment1, Environment2)  # declare two Likert items
#> Likert registration set for 'Environment1', 'Environment2' 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")
  jscreen(community)                              # Sub-class shows "Likert"
#> Data Screening
#>   Cases: 100 
#>   Variables: 15 
#>   Cases with missing data: 30 
#>   Variables with outliers: 0 
#> 
#> Variable Types
#> Variable        jstats Class  Sub-class   Source         Unique Values
#> --------------  ------------  ----------  -------------  -------------
#> RespondentID    Categorical   identifier                           100
#> Income          Numeric                                             52
#> Education       Categorical   5-category                             5
#> Age             Numeric                                             41
#> WellbeingScore  Numeric                                             43
#> Volunteer       Categorical   dichotomy                              2
#> OwnsHome        Categorical   dichotomy*                             2
#> Smoker          Categorical   dichotomy                              2
#> CommuteTime     Numeric                                             46
#> Region          Categorical   4-category                             4
#> Environment1    Categorical   Likert      User-declared              5
#> Environment2    Categorical   Likert      User-declared              5
#> Environment3    Categorical   Likert                                 5
#> Environment4    Categorical   Likert                                 5
#> Environment5    Categorical   Likert                                 5
#> * coded other than 0/1; mean is not a proportion
#> 
#> Missing Data & Outliers (outliers > 3 SD from mean)
#> Variable      Missing  % Missing
#> ------------  -------  ---------
#> Income              6        6.0
#> Education           6        6.0
#> Smoker              5        5.0
#> Environment1       12       12.0
#> Environment3       12       12.0
#> 
  jlikert(community, Environment1, remove = TRUE) # undo one
#> Likert registration removed for 'Environment1' in community.
  jlikert(community, NULL)                        # clear the registrations
#> Likert registrations cleared for community: Environment2.