Previous developments in our research

This article asks for fruitful points of connection between the theory of social worlds and arenas and ethnomethodology. Using the well-known ethnomethodological concept of doing gender as an example, I ask about deficits within the concept and how these could be overcome with the help of a pragmatist understanding of the situation, as laid out in Situational Analysis. 

Offenberger, Ursula (im Erscheinen). Un/doing gender in social worlds and arenas: Perspectives for aligning ethnomethodology with situational analysis. In Leslie Gauditz, Anna-Lisa Klages, Stefanie Kruse, Eva Marr, Ana Mazur, Tamara Schwertel, & Olaf Tietje (Hrsg.), Die Situationsanalyse als Forschungsprogramm. Wiesbaden: VS. 

The article explains how religious symbolization of gender is related to a common belief in the naturalness of gender orders. It asks how contemporary changes of modernization theories impact on the relationship between religion and gender. 

Offenberger, Ursula (2021a). Christentum und Geschlecht. Oder: Wie divers sind Eva und Adam? In Fahimah Ulfat & Ali Ghandour (Hrsg.), Sexualität, Gender und Religion in gegenwärtigen Diskursen. Wiesbaden: VS. 

This article reports on the process of creating a social science webcomic about the Hull House settlement in Chicago. It offers reflections on the appropriateness of scientific communication for the respective subject matter. 

Offenberger, Ursula (2021b). Verwandlung von Lehrstoff in einen Comic. Ein Experiment mit den Siedlerinnen von Hull House, Chicago. In Birgit Blättel-Mink (Hrsg.), Gesellschaft unter Spannung. Verhandlungen des 40. Kongresses der Deutschen Gesellschaft für Soziologie. 

Stefano Noventa and Daniel W. Heck, published in the Journal of Mathematical Psychology a proof of representation of basic probabilisitc models from Knowedge Structure Theory (specifically, the Basic Local Independence Model and the Simple Learning Model) within the general framework of Multinomial Processing Tree models. By highlighting such link and its implications for modeling violations of local stochastic independence in Item Response Theory, the authors hope to facilitate an exchange of theoretical results, statistical methods, and software across these different domains of mathematical psychology and psychometrics.

Heck*, D.W., Noventa*, S. (2020). Representing Probabilistic Models of
Knowledge Space Theory by Multinomial Processing Tree Models. Journal
of Mathematical Psychology, 96. DOI: 10.1016/j.jmp.2020.102329.

_{*shared co-first authorship}

This article should help readers in three ways: to assess the significance of qualitative methods and social science theories for interdisciplinary health research, to see the importance of a focus of health services research on the role of patient organisations and movements, and to understand that health research that is less strongly oriented towards instrumental use and direct application orientation can also provide useful extensions of perspectives for the design of health care in the future. 

Offenberger, Ursula (2020). Perspektiven und Potenziale qualitativer Gesundheitsforschung. Ein Plädoyer für interdisziplinäre Brückenschläge. Das Gesundheitswesen. 

Augustin Kelava and Holger Brandt published a new nonlinear dynamic latent class structural equation model (NDLC-SEM) framework in the Structural Equation Modeling Journal. The NDLC-SEM is capable of intra-individual psychological processes (e.g., changes in affective states as trajectories in mathematics studies), which for example could predict a drop-out. These processes are decomposed into parts which include individual-specific components (e.g., vulnerabilities, stable risk factors such as personality factors or cognitive abilities) and time-specific components. The NDLC-SEM acts as a very comprehensive framework that allows to integrate information of different data-levels and flexible relationships between variables (e.g., specific interactions).

Kelava, A. & Brandt, H. (2019). A nonlinear dynamic latent class structural equation model. Structural Equation Modeling: A Multidisciplinary Journal, 26(4), 509-528.  doi: 10.1080/10705511.2018.1555692