Irish Social Science Data Archive
Project: I am doing my final year project as a fourth year student in UL on this data and would like to use it for my own work to draw some simple maths based conclusions for my own project.
Project (2016): I intend to use the GUI dataset as part of my dissertation work for my Msc in child and youth studies. My research will be a mixed methods approach also using the qualitative dataset which I received last year as part of my course.
Project: Test application of methods for multiple imputations for categorical time-series data to time-diary data.
Project: I intend to explore the data set and use it as secondary data as part of my own research in the area of early intervention and prevention. I hope to explore the data and be able to draw conclusions to add to our knowledge in these areas.
Project: The GUI data will be used to inform the protocol of the CRNINI-PEI Research Initiative. Much of data being prepared for the archives shares population characteristics/topic area with the GUI data. I would like to examine how the GUI team prepared their data with the intention of preparing our CRNINI-PEI data to be compatible for comparative analysis by new users of the archived collections.
Project: We are working on an EPA/HSE funded project entitled Green and blue spaces and health: a health-led approach (2016-SE- DS-14) and we are looking at modelling the relationships between different health indicators and potential access to green and blue infrastructure (GBI) across two different time-periods. We have identified GUI as a useful means to pick up on longitudinal health data for a sub-section of society, namely children, and to additionally access, through GUI, changes in children’s health from ages 9 to 13. Given that there is a form of spatial tag with the data, we can then model – for selected areas/scales – the potential relationship between children’s health and modelled access to GBI
Project: Used to examine the experience of negative life events using Latent Class Analysis, and therefore the possibility of finding meaningful, homogenous sub-groups of people who experience multiple, similar experiences. These sub-groups would then be further examined in terms of their demographic profile, or other psychological factors available within the data.
Project (2016): Currently I am working on applying profiling methods, such as cluster analysis, latent class analysis and latent transition analysis, to waves 1 and 2 of the Irish longitudinal dataset Growing Up in Ireland as part of my PhD. I would like to apply these profiling methods to multiple lifestyle behaviour variables available in the GUI study and investigate the relationships between the identified profiles and other health related and socio-economic correlates. It is also of interest to use latent transition analysis to track how the identified profiles change between wave I, wave2 and wave 3.