Units sampled from finite populations typically come with different inclusion probabilities. Together with additional preprocessing steps of the raw data, this yields unequal sampling weights of the observations. Whenever indicators are estimated from such complex samples, the corresponding sampling weights have to be taken into account. In addition, many indicators suffer from a strong influence of outliers, which are a common problem in real-world data. The R package laeken is an object-oriented toolkit for the estimation of indicators from complex survey samples via standard or robust methods. In particular the most widely used social exclusion and poverty indicators are implemented in the package. A general calibrated bootstrap method to estimate the variance of indicators for common survey designs is included as well. Furthermore, the package contains synthetically generated close-to-reality data for the European Union Statistics on Income and Living Conditions and the Structure of Earnings Survey, which are used in the code examples throughout the paper. Even though the paper is focused on showing the functionality of package laeken, it also provides a brief mathematical description of the implemented indicator methodology.

Indicators, R, Robust estimation, Sample weights, Survey methodology
hdl.handle.net/1765/83353
Journal of Statistical Software (Online)
Erasmus School of Economics

Alfons, A, & Templ, M. (2013). Estimation of social exclusion indicators from complex surveys: The R package laeken. Journal of Statistical Software (Online), 54(15), 1–25. Retrieved from http://hdl.handle.net/1765/83353