Professor Partha Lahiri is a Professor in the Joint Program in Survey Methodology (JPSM) and Department of Mathematics at the University of Maryland at College Park, USA. Prior to coming to Maryland, Professor Lahiri was the Milton Mohr Distinguished Professor of Statistics at the University of Nebraska-Lincoln. Professor Lahiri’s research on small area estimation has […]
Professor Danny Pfeffermann is the National Statistician and Head of the Central Bureau of Statistics in Israel. He is also Professor of statistics at the University of Southampton, UK, and Professor Emeritus at the Hebrew University of Jerusalem, Israel. Professor Pfeffermann is a past President of the Israel Statistical Society and past President of the International Association of Survey Statisticians (IASS). […]
International demand for high quality, timely, small-domain data from official statistical agencies is steadily increasing and these small domain estimates can be extremely uncertain. Consequently, there is an expanding need for innovative methods that increase the precision and level of usability in publicly available data. In addition, enabling data users to obtain stable estimates for […]
The session – granted by the Tuscan Interuniversity Centre Advanced Statistics for Equitable and Sustainable Development “Camilo Dagum” (http://www.centrodagum.it) – aims at highlighting the importance and relevance of local data in welfare studies focusing on the limits and the potentialities of SAE methods in producing new data on welfare and wellbeing indicators at local level. […]
Small area estimation (SAE) has received considerable attention in recent years due to growing demand for reliable small area statistics that are needed in formulating policies and programs, allocation of government funds, regional planning, marketing decisions at local level, and other uses. Without any doubt, small area estimation is now one of the fastest growing […]
Face-to-face multistage cluster probability surveys are the gold standard for obtaining reliable information at the national level. However, most of the policy decisions are made at the local level such as states, counties, or health service areas. In national surveys, due to sampling procedures such as probability proportion to size selection methodology, there is no […]
The mapping of disease incidence and prevalence has long been a part of public health, epidemiology, and the study of disease in human populations. In this area, there have been always many challenge of obtaining reliable statistical estimates of local disease risk based on counts of observed cases within small administrative districts or regions coupled […]
Confidentiality is among the main themes of SAE 2017. On the other hand, the subject field is relatively new in the context of SAE, especially from a research point of view. The main purpose of this invited session is to engage this field of increasing importance and encourage research in confidentiality and related topics in […]
This session will focus on practical issues encountered in small area estimation that are new in the sense that they have been tackled in some recent work only. Three original topics will be addressed, to show the diversity and importance of the issues that still require theoretical and methodological research in small area estimation. The […]
The poster session will take place during the conference reception in the Tower Zamansky, that offers a panoramic view on Paris.
This session contains four contributions of Bayesian methods to small area estimation. The talks give methodological developments and applications related to quantile and semi parametric regression, mapping environmental indicators and sample size determination.
This session presents some small area estimation methodologies designed to treat situations where data have special characteristics, like: (1) coming from different sources (2) being geocoded, (3) containing information about individual level viewing exposures from television and digital media by PC in big data problems, and (4) integrating macro-level National Accounts data with micro-level survey […]
This session starts with a contribution dealing with fitting small area unit-level and area-level models under informative sampling design and nonignorable nonresponse. The second contribution studies how to treat measurement errors in small area estimation by investigating functional, structural and naive models approaches. The third contributions give some proposals about the estimation of sampling variances […]
This session contains three contributions dealing with benchmarking and calibration. The first contribution gives constrained empirical Bayes estimation in multiplicative area-level models with risk analysis under an asymmetric loss function. The second contributions introduces benchmark estimators for a small area mean under a one-fold nested regression model. Finally, the third contribution gives a two-level hybrid […]
This session contains three contributions of Bayesian methods to small area estimation. The talks give methodological developments and applications related to small area models with misclassified covariates, non ignorable missing values in nested error regression models and Beta regression models for small area estimation of proportions.
This session contains three contributions of robust methods to small area estimation. The talks give methodological developments and applications related to estimation of quantiles based on Fay-Herriot models, new model-based method that minimizes density power divergences and new bias calibration approaches for robust estimation of inequality indices.
Diagnostic and validation in a very important part of statistical data analysis when applying model based method. This section presents three contributions introducing Diagnostic and validation tools for area-level linear and nonlinear mixed models. The contributions contains applications to real data sets for illustrating the use of the proposed methodologies.
Poverty estimation is a field of great interest in small area estimation. This session contains three contributions that introduce some new methodologies and that give interesting comparisons of alternative methodologies under different scenarios.
Time and space correlation is a powerful way of borrowing strength and improving the efficiency of small area estimators. This section contains three contributions that introduce some new methodologies that borrow strength across areas and across time and/or that take into account for spatial correlations. The contributions contain applications to estimating survey discontinuities, to data […]