Book release - Modeling Psychophysical Data in R (Michel Hoen )

Subject: Book release - Modeling Psychophysical Data in R From: Michel Hoen <michel.hoen@xxxxxxxx> Date: Tue, 11 Sep 2012 07:50:11 +0200 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY> This is a multipart message in MIME format. ------=_NextPart_000_00AC_01CD8FF2.1387B1D0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit We would like to announce the imminent publication of the book "Modeling Psychophysical Data in R" (2012) Kenneth Knoblauch & Laurence T. Maloney, Springer ISBN: 978-1-4614-4474-9. 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. An electronic version is already available if purchased at <http://www.springer.com/statistics/computational+statistics/book/978-1-4614 -4474-9> http://www.springer.com/statistics/computational+statistics/book/978-1-4614- 4474-9 where sample pages can also be viewed (see also, <http://mpdir.r-forge.r-project.org/> http://mpdir.r-forge.r-project.org/). It can currently be ordered from Amazon and other online book sellers at a slight discount <http://www.amazon.com/Modeling-Psychophysical-Data-Kenneth-Knoblauch/dp/146 1444748> http://www.amazon.com/Modeling-Psychophysical-Data-Kenneth-Knoblauch/dp/1461 444748 Ken Knoblauch & Larry Maloney Kenneth Knoblauch Inserm U846 Stem-cell and Brain Research Institute Department of Integrative Neurosciences 18 avenue du Doyen Lepine 69500 Bron France ------=_NextPart_000_00AC_01CD8FF2.1387B1D0 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable <html xmlns:v=3D"urn:schemas-microsoft-com:vml" = xmlns:o=3D"urn:schemas-microsoft-com:office:office" = xmlns:w=3D"urn:schemas-microsoft-com:office:word" = xmlns:m=3D"http://schemas.microsoft.com/office/2004/12/omml" = xmlns=3D"http://www.w3.org/TR/REC-html40"><head><meta = http-equiv=3DContent-Type content=3D"text/html; = charset=3Dus-ascii"><meta name=3DGenerator content=3D"Microsoft Word 14 = (filtered medium)"><style></style></head><body lang=3DFR link=3Dblue = vlink=3Dpurple><div class=3DWordSection1>We would like to announce the imminent publication of the = book<o:p></o:p><o:p> </o:p>"Modeling Psychophysical Data in R" = (2012) Kenneth Knoblauch & Laurence T. Maloney, = Springer<o:p></o:p>ISBN: = 978-1-4614-4474-9.<o:p></o:p><o:p> </o:p>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.<o:p></o:p>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.<o:p></o:p><o:p> </o:p>An electronic version is already available if purchased = at<o:p></o:p><o:p> </o:p><a = href=3D"http://www.springer.com/statistics/computational+statistics/book/= 978-1-4614-4474-9">http://www.springer.com/statistics/computational+statistics/= book/978-1-4614-4474-9</a><o:p></o:p><o:p> </o:p>where sample pages can also be viewed (see also, <a = href=3D"http://mpdir.r-forge.r-project.org/">http://mpdir.r-forge.r-project.org/</a>). It can currently be ordered from Amazon and other online = book sellers at a slight discount<o:p></o:p><o:p> </o:p><a = href=3D"http://www.amazon.com/Modeling-Psychophysical-Data-Kenneth-Knobla= uch/dp/1461444748">http://www.amazon.com/Modeling-Psychophysical-Data-Kenneth-K= noblauch/dp/1461444748</a><o:p></o:p><o:p> </o:p>Ken Knoblauch & Larry Maloney<o:p></o:p><o:p> </o:p>Kenneth = Knoblauch<o:p></o:p>Inserm U846<o:p></o:p>Stem-cell and Brain Research = Institute<o:p></o:p>Department of = Integrative Neurosciences<o:p></o:p>18 = avenue du Doyen Lepine<o:p></o:p>69500 = Bron<o:p></o:p>France<o:p></o:p></div></body></html> ------=_NextPart_000_00AC_01CD8FF2.1387B1D0--

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