MLDS: Maximum likelihood difference scaling in R

Kenneth Knoblauch, Laurence T. Maloney

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)1-26
Number of pages26
JournalJournal of Statistical Software
Issue number2
StatePublished - Mar 2008


  • Difference scaling
  • GLM
  • Proximity
  • Psychophysics
  • Sensory magnitude
  • Signal detection theory

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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