Using R-Indicators to Address Response Bias: Evidence From the Longitudinal Surveys of Australian Youth

Abstract

This study uses representative indicators or ‘R-indicators’ as survey quality measures to investigate the possible risk of biased estimators in the latest Longitudinal Surveys of Australian Youth (LSAY) cohort. Using data from the first four waves of the cohort, R-indicators are used to measure how the response composition differs from that of the original sample. We present R-indicators for each survey wave, providing a comparable measure to investigate the quality and level of representativeness of the data over time. We also compute partial R-indicators for a range of auxiliary variables, including state, sector, location, sex, Indigenous status, socio-economic status (SES), mathematics and reading achievement scores and immigration status, to identify groups requiring further targeting in the sampling process. The effects of other activities undertaken to increase the sample size and improve the quality of the data are also explored. These include recruiting a top-up sample and re-engaging with non-respondents using additional efforts such as offering incentives. The article concludes by identifying respondent subgroups that need to be targeted or prioritised for follow-up in future waves. Examples of strategies we have used to engage the identified subgroups are also discussed.