indexSelfConstruction {OpenRepGrid} | R Documentation |
Self construction profile
Description
TBD
Usage
indexSelfConstruction(
x,
self,
ideal,
others = c(-self, -ideal),
method = "euclidean",
p = 2,
normalize = TRUE,
round = FALSE
)
Arguments
x |
A |
self |
Numeric. Index of self element. |
ideal |
Numeric. Index of ideal element. |
others |
Numeric. Index(es) of self related "other" elements (e.g. father, friend). |
method |
The distance or correlation measure:
|
p |
The power of the Minkowski distance, in case |
normalize |
Normalize values? |
round |
Round average rating scores for 'others' to closest integer? |
Value
List object of class indexSelfConstruction
, containing the results from the calculations:
-
grid
: Reduced grid with self, ideal and others -
method_type
: method type (correlation or distance) -
method
: correlation or distance method used -
self_element
: name of the self element -
ideal_element
: name of the ideal element -
other_elements
: name(s) of other elements -
self_ideal
: measure between self and ideal -
self_others
: measure between self and others -
ideal_others
: measure betwen ideal and others
References
TBD
Examples
# using distance measures
indexSelfConstruction(boeker, 1, 2, c(3:11), method = "euclidean")
indexSelfConstruction(boeker, 1, 2, c(3:11), method = "manhattan")
indexSelfConstruction(boeker, 1, 2, c(3:11), method = "minkowski", p = 3)
# using correlation measures
indexSelfConstruction(boeker, 1, 2, c(3:11), method = "pearson")
indexSelfConstruction(boeker, 1, 2, c(3:11), method = "spearman")
# using not-normalized distances
indexSelfConstruction(boeker, 1, 2, c(3:11), method = "euclidean", normalize = FALSE)
# printing the results (biplot only works with)
cp <- indexSelfConstruction(boeker, 1, 2, c(3:11))
cp$grid # grid with self, ideal and others
biplot2d(cp$grid, center = 4) # midopoint centering