Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
The network approach is increasingly employed to explore relationships among concepts, specifically the relationships between co-occurring health conditions (e.g., binary health condition indicators from hospital episode data) and the relationships between psychological variables (continuous scales from survey data). Given the multitude of approaches available for constructing and analyzing such networks and their application across different fields of study, determining the most appropriate methods and analyses can be challenging.
In this workshop, we will cover:
Theoretical Frameworks: An overview of the theoretical basis for applying network analysis to study relationships among health conditions or individual attributes.
Methodological Approaches: An exploration of existing methodologies for constructing networks and robustness testing of their estimations.
Analytical Techniques: A comprehensive set of analyses applicable to co-occurrence or correlation networks, including basic descriptive analysis, filtering methods, community detection, centrality analysis, and network comparisons.
We will offer a critical assessment of methods tailored to specific types of data and interpretations. Practical demonstrations will cover a range of methodological options and the various R packages to conduct them. In the final segment of the workshop, participants are encouraged to discuss the application of these methods to their specific datasets.
Names and contact information of organizers:
Srebrenka Letina; Srebrenka.letina@glasgow.ac.uk
Mark McCann; Mark.Mccann@glasgow.ac.uk
Length of the workshop: 3 hours
Maximum number of attendees: 30
Presentations
Co-occurrence and Correlation Networks
Srebrenka Letina, Mark McCann
The network approach is increasingly employed to explore relationships among concepts, specifically the relationships between co-occurring health conditions (e.g., binary health condition indicators from hospital episode data) and the relationships between psychological variables (continuous scales from survey data). Given the multitude of approaches available for constructing and analyzing such networks and their application across different fields of study, determining the most appropriate methods and analyses can be challenging.
In this workshop, we will cover:
Theoretical Frameworks: An overview of the theoretical basis for applying network analysis to study relationships among health conditions or individual attributes.
Methodological Approaches: An exploration of existing methodologies for constructing networks and robustness testing of their estimations.
Analytical Techniques: A comprehensive set of analyses applicable to co-occurrence or correlation networks, including basic descriptive analysis, filtering methods, community detection, centrality analysis, and network comparisons.
We will offer a critical assessment of methods tailored to specific types of data and interpretations. Practical demonstrations will cover a range of methodological options and the various R packages to conduct them. In the final segment of the workshop, participants are encouraged to discuss the application of these methods to their specific datasets.
