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	~~Notions~~ for ~~CCI4~~		=== Methodological advances on vulnerability and the life course ===

			Leader: André Berchtold<br>
			Support: Kevin Emery<br><br>
			This cross-cutting issue develops strategies for innovative longitudinal empirical analyses and new methods to study vulnerability across the course of life, at both individual and population levels. Five main themes are addressed:<br><br>
			'''1. Sampling design, modes of data collection and their effects'''<br>
			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.<br><br>
			'''2. Conceptualisation and measurement of vulnerability'''<br>
			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.<br><br>
			'''3. Analytical methods for longitudinal and network data'''<br>
			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?<br><br>
			'''4. Qualitative and mixed (quali-quanti) methods'''<br>
			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.<br><br>
			'''5. Data organisation and data sharing'''<br>
			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.<br><br>
			'''References'''<br>
			Bernardi, L. (2011). A mixed-method social networks study design for research on transnational families. LIVES Working Papers, 2011(3), 1-13.<br>
			Madero Cabib, I., Gauthier, J. - A., & Le Goff, J. - M. (2016). The influence of interlocked employment-family trajectories on retirement timing. Work, Aging and Retirement. 2(1), 38-53<br>
			Morselli, D., Berchtold, A., Suris, J.-C., Berchtold, A., (2016). On-line life history calendar and sensitive topics: A pilot study. Computers in Human Behavior. 58, pp. 141-149.<br>
			Oris, M., Roberts, C., Joye, D., Ernst Stähli, M. (2016). Surveying human vulnerabilities across the life course. Life Course Research and Social Policies. 242 p. New York: Springer.<br>
			Studer, M., & Ritschard, G. (2016). What matters in differences between life trajectories: A comparative review of sequence dissimilarity measures. Journal of the Royal Statistical Society: Series A (Statistics in Society), Vol. 179(2), pp. 481-511.

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Livesadmin at 14:09, 29 September 2020

Livesadmin: Created page with "Notions for CCI4"