Research Topics
■ Development of statistical data analysis methods in behavioral science
■ Methodological research on multivariate analysis, statistical causal inference, and mathematical psychology

　The field that conducts research and development of statistical analysis methods for analyzing psychological and behavioral data is referred to as psychometrics. From this field, various statistical analysis methods, collectively known as multivariate analysis, have emerged and evolved. Examples include factor analysis, structural equation modeling, multidimensional scaling, and correspondence analysis. Research themes in this field involve improving existing analytical methods and developing new ones. While formulas-based methods might give the impression of being well-established, in reality, there is still much room for improvement in existing methods, and there are numerous undeveloped methods that one might wish existed, making the research themes abundant. Additionally, mathematical psychology, which attempts to represent the mechanisms of the mind such as perception, memory, thought, and emotion through mathematical formulas, is also a subject of study. Furthermore, research is conducted on statistical causal inference, which estimates causal relationships (the relationships between cause and effect) from observed data. While studies in these areas require mathematics such as linear algebra, calculus, and probability theory, more important than mathematical skill is the need for "free imagination" and "innovative thinking.”