%0 Journal Article %J Journal of the Royal Statistical Society: Series A %D 2008 %T Alleviating Linear Ecological Bias and Optimal Design with Subsample Data %A Adam Glynn %A Jon Wakefield %A Mark Handcock %A Thomas Richardson %X In this paper, we illustrate that combining ecological data with subsample data in situations in which a linear model is appropriate provides two main benefits. First, by including the individual level subsample data, the biases associated with linear ecological inference can be eliminated. Second, we can use readily available ecological data to design optimal subsampling schemes, so as to maximize information about parameters. We present an application of this methodology to the classic problem of estimating the effect of a college degree on wages, showing that small, optimally chosen subsamples can be combined with ecological data to generate precise estimates relative to a simple random subsample. %B Journal of the Royal Statistical Society: Series A %V 171 %P 179-202 %G eng %N 1