A First Tour through R by Example.- Modeling in R.- Signal Detection Theory (SDT).- The Psychometric Function: Introduction.- The Psychometric Function: Continuation.- Classification Images.- Maximum Likelihood Difference Scaling (MLDS).- Maximum Likelihood Conjoint Measurement (MLCM).- Mixed-Effect Models.- Some Basics of R.- Statistical Background.- References.- Index.
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.
Although the applications of R presented in this text are focused on the analysis of psychophysical data, the methodology is generalizable to many other areas in statistics. For example, coverage of solving equations by maximum likelihood and the various general linear model functions are applicable in many situations which occur in statistical data analysis. I found the discussion of ROC analysis to be very useful in many other areas of statistics also. Therefore, I would recommend this text to anyone who works with, or is interested in, psychophysical data or even to anyone who wants to increase their knowledge of R. Technometrics, 56:1 2014
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