This project, supported by Portugal 2020 funds, aims to support BRU-Iscte institutional capacities in submitting applications to European competitive funding, namely within the Horizon 2020 programme. With this support, BRU-Iscte has drafted a strategic plan for 2019-2022 with regards to the submission of applications to competitive European funding schemes in areas of key interest for BRU research activities.

Using cutting-edge methodology and, when required, developing new methods, this project aims to improve the skills of those involved in longitudinal research, in particular methodologists and researchers in the social sciences. The proposed work addresses both important methodological questions and substantive issues. In particular, data from the Consortium of Household panels for European socio-economic Research (CHER) will be used to illustrate methodological challenges when modelling socio-economic change. Using exemplars from the substantive research this project will present strategies for choosing the most appropriate statistical methods for analysing data with a longitudinal structure, taking into account measurement errors and complex survey designs.Survey data is the main source of information when regarding demographic and social characteristics of the population, economic activity, lifestyle patterns, and public opinion. Longitudinal survey data allow for the periodic measurement of individual’s demographic and socio-economic changes in their conditions. In panel studies the same and (or) different variables are measured on the same units at least at two time points. Panel data is particularly adequate for investigating changes at the individual level. Longitudinal studies also allow us to distinguish the degree of variation in the response variable across time for one person from the variation among subjects and, in principle, also to make stronger causal interpretations mainly regarding inferences about changes, by determining the direction and magnitude of causal relationships. Furthermore, panel data is capable, for example, of providing measures before and after important social and economic policy events. Several statistical approaches have been used to analyse and model panel survey data. These include random effects models, transition models (as is the case of graphical chain models), structural equation models and latent curve growth models. Long...