Description Usage Arguments Details Examples
This function matches pairs of names based on similarity to create a set of trials. Names are matched, such that each name is only used once and the sum of the distances over all names in total is minimized.
1 | match.partition(split, discard = 0, subset = filter.names(), ...)
|
split |
The name of the rating on which the split should be performed |
discard |
The percentage of names too close to the median which should be discarded (default: 0, i.e. keep all names) |
subset |
An optional subset on which the split should be done. If this is left out, the split will be created on all names. |
... |
Arguments passed on to
|
Normally the principal components are used for matching names, but other ratings can also be added and emphasized to create sets of names which are more similar along a special set of ratings.
Note: This function is a shortcut to create the split using
partition.names
and match the pairs using
match.split
in a single step.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Just match names split on Sex rating
m <- match.partition(Sex)
m
# Match names, but discard some which are ambigous in terms of Sex
m <- match.partition(Sex, discard = 0.2)
m
# First filter unfamiliar and foreign names
s <- filter.names(Familiarity >= 0.5, Nationality >= 0.5)
m <- match.partition(Sex, discard = 0.2, subset=s)
m
# Emphasize on competence and intelligence (weighted 10 times)
m <- match.partition(Sex, discard = 0.2, subset=s, Competence=10, Intelligence=10)
m
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.