Wednesday 2nd December 2020, 11:10–11:25 (Australia/Sydney), Zoom Breakout Room 1
Dual frame surveys using mobile and landline telephone numbers have been the predominant method of sampling for CATI interview studies in Australia for several years now, however neither frame is without its problems. Landline telephones can only be used to access 49% of the population, with coverage heavily skewed towards older age groups. Mobile telephones are not inherently linked to a geographic location meaning that obtaining geographically targeted samples is expensive, often prohibitively so. Commercial sample providers have recently improved their offering for “listed” mobile phone numbers with geographical information attached, however these lists also have coverage errors particularly for younger age groups. This presentation reports on work carried out for a large state-level survey to determine an optimum blend of sample sources including listed and RDD mobile phones alongside landline sample. The survey is state-wide, but includes a sample quotas for each of the 79 LGAs in the state, so requires a large degree of geographical targeting. Several simulations were carried out using a variety of different sample mixes to determine the most cost-effective solution.
Dina is a professional statistician with over 20 years of experience and a track record of achievement in leadership and technical roles at the Social Research Centre, Monash University, Australian Bureau of Statistics, and Biostatistics and Clinical Trials Centre at Peter MacCallum Cancer Centre. Dina’s statistical interests include the use of calibration and blending methods to improve accuracy of the non-probability samples, establishment and maintenance of the first Australian Online Probability panel and complex business survey design and weighting. Throughout her career she has worked through every stage of statistical data collection including design, system development, contact with respondents, data editing, estimation and output, in a wide variety of domains including demographic, labour, business and price index statistics. Dina’s educational background includes 1st Class Honours degree in Statistics and PhD in Business Systems from
Monash University with an emphasis in applied Operations Research and Process Engineering. Dina is Accredited Statistician (AStat) member of the Statistical Society of Australia (SSA) and is a member of the American Association for Public Opinion Research (AAPOR).
Sebastian joined the Social Research Centre as a Senior Data Analyst in November 2009. During that period he has worked on our major longitudinal survey of income support customers (the Stepping Stones Survey) undertaken for the Department of Education, Employment and Workplace Relations as well as playing an important data management and statistical consulting role in major projects such as the Student Outcomes Survey, the Early Childhood Education and Care Workforce Census, and the Quality Indicators in Learning and Teaching (QILT) suite of projects. He has also played a major role in establishing company practices around weighting for dual-frame surveys.