Head: PD Dr. Daniel Seddig
The Methods Department deals with the research methods and statistical procedures used in criminology for the observation, measurement, and analysis of crime phenomena. In three focus areas, methodological developments and questions are addressed from various perspectives.
Focus Areas
The three focus areas are methodological research (1), data integration and documentation of data and findings from past and ongoing research projects (2), and consultation and methods training (3). The focus areas are intended to encompass a diverse range of methods and have the goal of leveraging current challenges in various areas of empirical research as opportunities for the KFN. To achieve this, methodological discourses in psychology, sociology, and political science are actively pursued, and own (third-party funded) projects are initiated.
Methodological Research
The focus area Methodological Research concentrates on alternative data sources, innovative research designs, and new analytical methods. In particular, the virtual world has gained significant importance as a source of new insights, with data often being unplanned, unstructured, and available in large quantities. For criminological research, digital behavioral data, or georeferenced crime data, for example, hold great potential. Innovative study designs are particularly present in the realm of virtual and video scenarios, international comparative approaches, and mixed-methods approaches. Regarding analytical methods, the focus lies on developments in structural equation modeling, analysis of count data, multilevel analysis, and machine learning (artificial intelligence).
Data Integration and Documentation
The focus area Data Integration and Documentation aims to gain new insights into criminal phenomena by integrating and aggregating data from various KFN studies on self-reported crime. For example, using data from the Lower Saxony Survey, self-reported delinquency and victimization of adolescents are explored over time on aggregated levels (e.g., Lower Saxony districts). This is closely linked to the study of statistical methods for specific types of data.
Furthermore, a comprehensive data structure is created, summarizing various KFN studies. Information from different contexts and time points is to be analyzed in a data-driven and exploratory way using machine learning methods to identify (previously undiscovered) patterns of relationships.
Another goal is the documentation of the instruments and scales, as well as the expansion of existing knowledge with methodologically relevant categories for measurement quality. This includes the analysis of validity and reliability criteria, response patterns and outliers, scale conversion, and the comparability of measurements over time or between different groups of respondents.
Consultation and Methods Training
The focus area Consultation and Methods Training aims to actively support research units and staff in the planning and implementation of research projects. At the same time, the Methods Department is committed to training and promoting academic talent. As part of the KFN MethodLab, biannual methods workshops are planned, which include both methodological and analytical training as well as a lecture series or mini-conference.
Current research projects
