Methodological advances on vulnerability and the life course
1. Sampling design, modes of data collection and their effects
This theme welcomes the development and improvement of diverse sampling methods such as mixing modes of data collection, improving methods of collecting personal and family network data, and setting up sophisticated data collection methods allowing a comparison of networks drawn from name, position and resource generators; but also of life calendars and the evaluation of the impact of missing values in longitudinal data. An important question within this topic concerns the feasibility and reliability of online life-history calendars.
2. Conceptualisation and measurement of vulnerability
The conceptualisation and measurement of vulnerability is at an early stage and is clearly in need of further development. A particular point of interest is how to assess the multidimensional and and dynamic nature of vulnerability through qualitative and quantitative studies.
3. Analytical methods for longitudinal and network data
More work needs to be done on analytical methods of handling longitudinal and network data. Sequence analysis and Markov-based models are among those so far developed by LIVES, but other approaches are welcome. Key research questions within this topic are a) how to combine the results from different approaches, and b) are there any alternatives to the dissimilarity-based methods for the classification of data sequences?
4. Qualitative and mixed (quali-quanti) methods
Although qualitative and mixed quali-quanti methods are seen as ways of opening up new research approaches, to our knowledge there is currently no platform on which they are discussed and investigated. Within this topic, the intention is to propose such a platform to stimulate the development of the effective use of mixed methods. An open question of particular interest lies in the definition of guidelines to determine when mixed methods would be preferable to purely qualitative or quantitative approaches.
5. Data organisation and data sharing
This topic focuses on expressing the rules for describing and documenting the data collected within LIVES in operational terms. Thanks to this initiative, LIVES members now have easy access to most of the LIVES data sets. One remaining question is how to aggregate data from different studies run on the basis of different populations and sampling designs.