Modeling Psychophysical Data in R

  • Kenneth Knoblauch
  • Laurence T. Maloney

Part of the Use R! book series (USE R, volume 32)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Kenneth Knoblauch, Laurence T. Maloney
    Pages 1-20
  3. Kenneth Knoblauch, Laurence T. Maloney
    Pages 21-60
  4. Kenneth Knoblauch, Laurence T. Maloney
    Pages 61-105
  5. Kenneth Knoblauch, Laurence T. Maloney
    Pages 107-139
  6. Kenneth Knoblauch, Laurence T. Maloney
    Pages 141-166
  7. Kenneth Knoblauch, Laurence T. Maloney
    Pages 167-194
  8. Kenneth Knoblauch, Laurence T. Maloney
    Pages 195-228
  9. Kenneth Knoblauch, Laurence T. Maloney
    Pages 229-256
  10. Kenneth Knoblauch, Laurence T. Maloney
    Pages 257-301
  11. Back Matter
    Pages 303-367

About this book

Introduction

Many of the commonly used methods for modeling and fitting psychophysical data are special cases of statistical procedures of great power and generality, notably the Generalized Linear Model (GLM). This book illustrates how to fit data from a variety of psychophysical paradigms using modern statistical methods and the statistical language R. The paradigms include signal detection theory, psychometric function fitting, classification images and more. In two chapters, recently developed methods for scaling appearance, maximum likelihood difference scaling and maximum likelihood conjoint measurement are examined. The authors also consider the application of mixed-effects models to psychophysical data.

R is an open-source  programming language that is widely used by statisticians and is seeing enormous growth in its application to data in all fields. It is interactive, containing many powerful facilities for optimization, model evaluation, model selection, and graphical display of data. The reader who fits data in R can readily make use of these methods. The researcher who uses R to fit and model his data has access to most recently developed statistical methods.

This book does not assume that the reader is familiar with R, and a little experience with any programming language is all that is needed to appreciate this book. There are large numbers of examples of R in the text and the source code for all examples is available in an R package MPDiR available through R.
Kenneth Knoblauch is a researcher in the Department of Integrative Neurosciences in Inserm Unit 846, The Stem Cell and Brain Research Institute and associated with the University Claude Bernard, Lyon 1, in France. 

Laurence T. Maloney is Professor of Psychology and Neural Science at New York University. His research focusses on applications of mathematical models to perception, motor control and decision making.

Keywords

Mixed-Effect Models Neural Systems Psychometric Function Psychometry Psychophysics R Sensory Information Signal Detection Theory

Authors and affiliations

  • Kenneth Knoblauch
    • 1
  • Laurence T. Maloney
    • 2
  1. 1.Stem-cell and Brain Research Institute, Dept. of Integrative NeurosciencesINSERM U846BronFrance
  2. 2., Department of PsychologyNew York UniversityNew YorkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-4475-6
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-4474-9
  • Online ISBN 978-1-4614-4475-6
  • About this book