interest

The data come from a fabricated cognitive, personality, and vocational interested inventory. This data set can be used to demonstrate regression and structural equation modeling.

dataset

A suite of multivariate methods and data visualization
tools to implement profile analysis and cross-validation techniques described in
Davison & Davenport (2002) <DOI: 10.1037/1082-989X.7.4.468>, Bulut (2013), and other published and unpublished resources.
The package includes routines to perform criterion-related profile analysis, profile analysis
via multidimensional scaling, moderated profile analysis, profile analysis by group, and a
within-person factor model to derive score profiles.

Christopher David Desjardins

profileR

Profile Analysis of Multivariate Data in R

interest function

A data frame with 250 rows and 33 variables:<dl class="dl-horizontal">
 <dt>gender</dt><dd>1 is female and 2 is male</dd>
 <dt>educ</dt><dd>Years of education</dd>
 <dt>age</dt><dd>Age, in years</dd>
 <dt>vocab</dt><dd>Vocabulary test</dd>
 <dt>reading</dt><dd>Reading comprehension</dd>
 <dt>sentcomp</dt><dd>Sentence completion</dd>
 <dt>mathmtcs</dt><dd>Mathematics</dd>
 <dt>geometry</dt><dd>Geometry</dd>
 <dt>analyrea</dt><dd>Analytical reasoning</dd>
 <dt>socdom</dt><dd>Social dominance</dd>
 <dt>sociabty</dt><dd>Sociability</dd>
 <dt>stress</dt><dd>Stress reaction</dd>
 <dt>worry</dt><dd>Worry scale</dd>
 <dt>impulsve</dt><dd>Impulsivity</dd>
 <dt>thrillsk</dt><dd>Thrill-seeking</dd>
 <dt>carpentr</dt><dd>Carpentry</dd>
 <dt>forestr</dt><dd>Forest ranger</dd>
 <dt>morticin</dt><dd>Mortician</dd>
 <dt>policemn</dt><dd>Police</dd>
 <dt>fireman</dt><dd>Fireman</dd>
 <dt>salesrep</dt><dd>Sales representative</dd>
 <dt>teacher</dt><dd>Teacher</dd>
 <dt>busexec</dt><dd>Business executive</dd>
 <dt>stockbrk</dt><dd>Stock broker</dd>
 <dt>artist</dt><dd>Artist</dd>
 <dt>socworkr</dt><dd>Social worker</dd>
 <dt>truckdvr</dt><dd>Truck driver</dd>
 <dt>doctor</dt><dd>Doctor</dd>
 <dt>clergymn</dt><dd>Clergyman</dd>
 <dt>lawyer</dt><dd>Lawyer</dd>
 <dt>actor</dt><dd>Actor</dd>
 <dt>archtct</dt><dd>Architect</dd>
 <dt>landscpr</dt><dd>Landscaper</dd>
</dl>

Format

Fabricated cognitive, personality, and vocational interest inventory — interest

A data frame with 250 rows and 33 variables:<dl class='dl-horizontal'>
 <dt>gender</dt><dd>1 is female and 2 is male</dd>
 <dt>educ</dt><dd>Years of education</dd>
 <dt>age</dt><dd>Age, in years</dd>
 <dt>vocab</dt><dd>Vocabulary test</dd>
 <dt>reading</dt><dd>Reading comprehension</dd>
 <dt>sentcomp</dt><dd>Sentence completion</dd>
 <dt>mathmtcs</dt><dd>Mathematics</dd>
 <dt>geometry</dt><dd>Geometry</dd>
 <dt>analyrea</dt><dd>Analytical reasoning</dd>
 <dt>socdom</dt><dd>Social dominance</dd>
 <dt>sociabty</dt><dd>Sociability</dd>
 <dt>stress</dt><dd>Stress reaction</dd>
 <dt>worry</dt><dd>Worry scale</dd>
 <dt>impulsve</dt><dd>Impulsivity</dd>
 <dt>thrillsk</dt><dd>Thrill-seeking</dd>
 <dt>carpentr</dt><dd>Carpentry</dd>
 <dt>forestr</dt><dd>Forest ranger</dd>
 <dt>morticin</dt><dd>Mortician</dd>
 <dt>policemn</dt><dd>Police</dd>
 <dt>fireman</dt><dd>Fireman</dd>
 <dt>salesrep</dt><dd>Sales representative</dd>
 <dt>teacher</dt><dd>Teacher</dd>
 <dt>busexec</dt><dd>Business executive</dd>
 <dt>stockbrk</dt><dd>Stock broker</dd>
 <dt>artist</dt><dd>Artist</dd>
 <dt>socworkr</dt><dd>Social worker</dd>
 <dt>truckdvr</dt><dd>Truck driver</dd>
 <dt>doctor</dt><dd>Doctor</dd>
 <dt>clergymn</dt><dd>Clergyman</dd>
 <dt>lawyer</dt><dd>Lawyer</dd>
 <dt>actor</dt><dd>Actor</dd>
 <dt>archtct</dt><dd>Architect</dd>
 <dt>landscpr</dt><dd>Landscaper</dd>
</dl>

interest: Fabricated cognitive, personality, and vocational interest inventory

Description

Usage

Arguments

Format