Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Keith T. Poole, Jeffrey B. Lewis, Howard Rosenthal, James Lo, Royce Carroll
Title: Recovering a Basic Space from Issue Scales in R
Abstract: basicspace is an R package that conducts Aldrich-McKelvey and Blackbox scaling to recover estimates of the underlying latent dimensions of issue scale data. We illustrate several applications of the package to survey data commonly used in the social sciences. Monte Carlo tests demonstrate that the procedure can recover latent dimensions and reproduce the matrix of responses at moderate levels of error and missing data.

Page views:: 1251. Submitted: 2012-08-08. Published: 2016-03-11.
Paper: Recovering a Basic Space from Issue Scales in R     Download PDF (Downloads: 543)
Supplements:
basicspace_0.17.tar.gz: R source package Download (Downloads: 97; 1MB)
v69i07.R: R replication code Download (Downloads: 137; 5KB)
DOI: 10.18637/jss.v069.i07

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.