This award will provide partial support for the 44th Annual Meeting of the Society for Mathematical Psychology to be held in Boston (Medford), MA at Tufts University on July 15-19, 2011. The Society for Mathematical Psychology Conference encourages the presentation of research in which mathematical, statistical, or simulation methods play a significant role in the development of hypotheses or the interpretation of experimental results in the behavioral, neural, and cognitive sciences. In addition, accepted research papers focus on theoretical developments clearly relating to substantive issues or methodologies of obvious use in psychology, cognitive science, cognitive neuroscience, and related areas and/or experimental results which bear directly on particular mathematical or simulation models of aspects of human behavior. This year's conference themes include: (1) Recent developments in the application of multidimensional signal detection theory; (2) Modern models of recognition memory; and (3) Applied significance of the foundations of probability theory. A preconference half-day meeting focusing on recruiting and retaining women in mathematical psychology will occur just prior to the start of the full Society meeting. Following the main conference, there will be a full-day workshop on building, fitting, and interpreting multinomial processing tree models from a diverse set of perspectives.
Mathematical psychology brings together social scientists, statisticians, mathematicians, and computer scientists to work on problems critical to behavioral scientists. Much transformational research has come from the mathematical psychology community, including mathematical models of brain function, memory, and decision-making, as well as the introduction of new methods for data analysis. While mathematical models improve our understanding of human behavior and provide formal structures for future scientific exploration, new and better methods for data analysis allow us to derive more accurate and nuanced conclusions from behavioral data. The annual meeting of the Society advances discovery and understanding. It promotes training and learning of new models and methods for analyzing behavioral data. It makes possible the broad dissemination of new findings important in all areas of psychology, as well as economics, political science, and sociology.
Conference features presentation of research in which mathematical, statistical, or simulation methods play a significant role in the development of hypotheses or the interpretation of experimental results in the behavioral, neural, and cognitive sciences. In addition, accepted research papers focus on theoretical developments clearly relating to substantive issues or methodologies of obvious use in psychology, cognitive science, cognitive neuroscience, and related areas and/or experimental results which bear directly on particular mathematical or simulation models of aspects of human behavior. This year's conference themes included: (1) Recent developments in the application of multidimensional signal detection theory; (2) Modern models of recognition memory, and (3) Applied significance of the foundations of probability theory. This year, a pre-conference half-day meeting focusing on recruiting and retaining women in mathematical psychology will occur just prior to the start of the full Society meeting. The key-note speaker for this pre-conference event was Barbara Dosher, from UC-Irvine, who was recently inducted into the National Academy of Sciences. Following the main conference, on Tuesday July 19 a full day workshop on the building, fitting, and interpreting multinomial processing tree models from a diverse set of perspectives was held. Mathematical psychology brings together social scientists, statisticians, mathematicians and computer scientists to work on problems critical to behavioral scientists. Much transformational research has come from the mathematical psychology community, including mathematical models of brain function, memory, and decision-making, as well as the introduction of new methods for data analysis. While mathematical models improve our understanding of human behavior and provide formal structures for future scientific exploration, new and better methods for data analysis allow us to derive more accurate and nuanced conclusions from behavioral data. The annual meeting of the Society advances discovery and understanding. It promotes training and learning of new models and methods for analyzing behavioral data. It makes possible the broad dissemination of new findings important in all areas of psychology, as well as economics, political science and sociology.
