Making multilevel data ideas more accessible

Abstract

Each year increasing amounts of data are being produced and there are growing trends towards data becoming more accessible, particularly online. Here we present a range of examples where data are conveniently arranged in multiple linked rectangles or data frames. They are often omitted from all but advanced statistics courses. However, they are common in practice, hence their omission leaves graduates poorly prepared for real world problems. The obvious example is a survey that is at multiple levels. Other examples include multiple time series with spatial data, where the spatial information is in a separate data frame; and data sets in a single rectangle (data frame) but where the analyses are on summary data. The statistical software, R-Instat, resulting from the African Data Initiative is designed to make it easy to handle such data.