NCRM International Visitor Exchange Scheme (IVES)
A Simulation of the Long Term Effects of an Adaptive Fieldwork Design in Longitudinal Surveys (2017 - 2018)
Alexandru Cernat (University of Manchester) (firstname.lastname@example.org) is visiting Nicole Watson (University of Melbourne).
Main objectives of the project are:
- Develop of a simulation study to understand the impact of different strategies of adaptive designs in longitudinal studies
- Write a research paper on the topic of adaptive designs and longitudinal studies
- Prepare a session on adaptive designs in longitudinal data at one of the major methodology conferences
- Discuss the development of a joint grant application
Survey data continues to be essential for the work of social scientists. This is also true for longitudinal data where multiple measurements are taken at different points in time for the same respondents. Nevertheless, in recent years increasing costs and non-response have put pressures on survey agencies to improve the way they collect data.
One of the proposed solutions is called the adaptive design approach. This implies the division of data collection in multiple stages and applying different strategies for particular groups of respondent and stages that maximizes their propensity to answer and/or minimize costs. While this approach has great potential it has been studied predominately with a cross-sectional focus ignoring the broader context of longitudinal studies. This is problematic as data collection in longitudinal studies have to consider at the same time both short term outcomes, such as participation at the current wave, as well as long term outcomes, for example participation in 5 years.
The present project aims to develop the framework of adaptive survey designs that accounts for both short term and long term outcomes in longitudinal studies. This will be done by developing a series of simulations that are based on data collected in the UK and Australia.
The research will help improve data collection in longitudinal studies, which is a major investment in the social sciences. It will also help improve the current literature in adaptive survey design and will enable more realistic decision making in data collection in general.