LEADER 00000cam 2200781Ki 4500 001 809852943 003 OCoLC 005 20181130031901.5 006 m o d 007 cr cnuunuuu 008 120913s2012 nyu ob 001 0 eng d 019 809479045a811044637a985059908a988802371a990731311 a1005812973a1058100469a1066436110 020 9781461444756q(electronic bk.) 020 1461444756q(electronic bk.) 020 z1461444748 020 z9781461444749 024 7 10.1007/97814614447562doi 035 (OCoLC)809852943z(OCoLC)809479045z(OCoLC)811044637 z(OCoLC)985059908z(OCoLC)988802371z(OCoLC)990731311 z(OCoLC)1005812973z(OCoLC)1058100469z(OCoLC)1066436110 040 GW5XEbengepnerdacGW5XEdUV0dYDXCPdZMCdCOOdE7BdCDX dOCLCQdDEBSZdTPHdOCLCQdOCLCOdOCLCQdVT2dZ5AdLIP dOCLCOdESUdOCLCQdIOGdOCLCOdOCLCAdN$TdOCLCAdOCLCQ dOCLCOdOCLCFdCEFdU3WdOCLCOdAU@dOCLCOdWYUdOCLCQ dOCLCA 049 MAIN 050 4 BF237b.K56 2012 072 7 COM0770002bisacsh 072 7 PSYx0290002bisacsh 072 7 UFM2bicssc 082 04 150.72/7223 100 1 Knoblauch, K.q(Kenneth)0http://id.loc.gov/authorities/ names/nb2003051891 245 10 Modeling psychophysical data in R /cKenneth Knoblauch, Laurence T. Maloney. 264 1 New York, NY :bSpringer,c2012. 300 1 online resource. 336 textbtxt2rdacontent 337 computerbc2rdamedia 338 online resourcebcr2rdacarrier 340 gpolychrome2rdacc0http://rdaregistry.info/termList/ RDAColourContent/1003 347 text file2rdaft0http://rdaregistry.info/termList/ fileType/1002 490 1 Use R! 504 Includes bibliographical references and index. 505 00 tA First Tour Through R by Example tModeling in R  tSignal Detection Theory tThe Psychometric Function: Introduction tThe Psychometric Function: Continuation  tClassification Images tMaximum Likelihood Difference Scaling tMaximum Likelihood Conjoint Measurement  tMixedEffects Models. 520 "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 mixedeffects models to psychophysical data. R is an opensource 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"Back cover. 650 0 Psychophysics0http://id.loc.gov/authorities/subjects/ sh85108501xStatistical methods.0http://id.loc.gov/ authorities/subjects/sh2001008679 650 0 Psychophysics0http://id.loc.gov/authorities/subjects/ sh85108501xComputer simulation.0http://id.loc.gov/ authorities/subjects/sh99005300 650 0 R (Computer program language)0http://id.loc.gov/ authorities/subjects/sh2002004407 650 0 PsychometricsxData processing.0http://id.loc.gov/ authorities/subjects/sh85108491 650 12 Psychophysicsxmethods.0https://id.nlm.nih.gov/mesh/ D011601Q000379 650 12 Psychophysicsxstatistics & numerical data.0https:// id.nlm.nih.gov/mesh/D011601Q000706 650 14 Statistics. 650 22 Computer Simulation.0https://id.nlm.nih.gov/mesh/D003198 650 22 Models, Statistical.0https://id.nlm.nih.gov/mesh/D015233 650 24 Statistics and Computing/Statistics Programs. 650 24 Statistical Theory and Methods. 650 24 Statistics, general. 650 24 Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. 653 4 Statistics. 653 4 Mathematical statistics. 653 4 Statistics and Computing/Statistics Programs. 653 4 Statistical Theory and Methods. 653 4 Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. 655 4 Electronic books. 700 1 Maloney, Laurence T.0http://id.loc.gov/authorities/names/ n95056098 776 08 iPrint version:w(OCoLC)794710040 830 0 Use R!0http://id.loc.gov/authorities/names/no2006017477 880 652000aMany 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 mixedeffects models to psychophysical data. R is an opensource� 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. 990 SpringerLinkbSpringer English/International eBooks 2012  Full Setc20181130yMaster record variable field(s) change: 6505OH1 990 SpringerLinkbSpringer English/International eBooks 2012  Full Setc20181123yMaster record variable field(s) change: 6505OH1 990 SpringerLinkbSpringer English/International eBooks 2012  Full Setc20181031yNew collection springerlink.ebooks20125OH1
