What are psychometric statistical methods

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In the field of statistical data analysis, the work of the Institute for Medical Psychology and Sociology focuses on the methods of psychometry, multivariate regression analysis and non-parametric statistics. Special importance is attached to the psychometric analysis of questionnaires that are routinely used in clinical practice. With the help of structural equation models and the methods of item response theory, we examine, for example, the psychometric properties of well-known instruments such as the SF-12 and SF-36 as well as the Quality Of Life after Brain Injury Questionnaire (QOLIBRI).

In the data analysis of clinical and epidemiological studies, special attention is paid to the so-called generalized mixed linear models (GLMM), which include a very wide range of model specifications for different data structures (e.g. nested designs, longitudinal data and repeated measurements as well as frequentistic and Bayesian methods) Event data).

Nonparametric methods in cross-section and longitudinal section are robust alternatives to conventional statistical models that can be applied to any data type with few assumptions. In this sense, only the distributions on which the empirical data is based are examined in the nonparametric data analysis in order to arrive at conclusions about the temporal course of diseases or health conditions under the influence of specific factors.

Another focus of the institute's work in the context of statistical data analysis is the use of the programming language and statistical environment R. In particular, we devote ourselves to the development of suitable functions or packages in the field of psychometry and multivariate regression analysis as well as the use of R in teaching .