Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
MLDS: Maximum Likelihood Difference Scaling in R | Knoblauch | Journal of Statistical Software
Authors: Kenneth Knoblauch, Laurence T. Maloney
Title: MLDS: Maximum Likelihood Difference Scaling in R
Abstract: The MLDS package in the R programming language can be used to estimate perceptual scales based on the results of psychophysical experiments using the method of difference scaling. In a difference scaling experiment, observers compare two supra-threshold differences (a,b) and (c,d) on each trial. The approach is based on a stochastic model of how the observer decides which perceptual difference (or interval) (a,b) or (c,d) is greater, and the parameters of the model are estimated using a maximum likelihood criterion. We also propose a method to test the model by evaluating the self-consistency of the estimated scale. The package includes an example in which an observer judges the differences in correlation between scatterplots. The example may be readily adapted to estimate perceptual scales for arbitrary physical continua.

Page views:: 3430. Submitted: 2007-04-17. Published: 2008-03-18.
Paper: MLDS: Maximum Likelihood Difference Scaling in R     Download PDF (Downloads: 3372)
MLDS_0.1-1.tar.gz: R source package Download (Downloads: 1252; 24KB)
v25i02.R: R example code from the paper Download (Downloads: 1962; 6KB)

DOI: 10.18637/jss.v025.i02

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.