This paper provides practical guidelines for the design and analysis of sample surveys that are to be used for small area estimation using regression type methods. It is based on the author's experience using small area estimation in a range of studies including small area modeling of employment and unemployment, small area estimation of poverty and small domain estimation of ethnicity, in a range of countries including USA, UK, Bangladesh, Philippines, Nepal, Cambodia, and New Zealand, and for feasibility studies in Bhutan and Timor-Leste. The importance of recognising at design stage that one of the uses of the survey data will or may be small area estimation, and identifying all the parameters that will require estimation (including variance components) will be discussed, as will issues of clarity of aim, data availability, and model choice at the analysis stage.

Keywords: Small area estimation; Sample design; Analysis of complex surveys

Biography: Stephen Haslett is Professor of Statistics at Massey University, New Zealand. He has interests in theoretical statistics especially in application of linear algebra, for example to sample surveys and mixed models. He has also had over 30 years experience in applied statistics (for example for the UN World Food Programme) in a range of countries including Azerbaijan, Vietnam, Samoa, Thailand, Kiribati, Vanuatu and has undertaken small area estimation projects in USA, UK, Bangladesh, Philippines, Nepal, Cambodia, and New Zealand, and sae feasibility studies in Bhutan and Timor-Leste.