Book Chapter

Modelling trends in digit preference patterns

Camarda, C. G., Eilers, P. H. C., Gampe, J.
In: Booth, J. G. (Ed.): Proceedings of the 24th International Workshop on Statistical Modelling, Ithaca 20 - 24 July, 2009, 81–88
Ithaca, NY, Cornell University, Department of Biological Statistics and Computational Biology (2009)


A two-dimensional generalization of a penalized composite link model is presented to model latent distributions with digit preference, where the strength of the misreporting pattern can vary over time. A general preference pattern is superimposed on a series of smooth latent densities, and this pattern is modulated for each measurement occasion. Smoothness of the latent distributions is enforced by a difference penalty on neighbouring coefficients. An L1-ridge regression is used for the common misreporting pattern, and an additional weighted least-squares regression extracts the modulating vector. The BIC is used to optimize the smoothing parameters. We present a simulation study and an application for demonstrating the performance of our model and its practical characteristics.
The Max Planck Institute for Demographic Research (MPIDR) in Rostock is one of the leading demographic research centers in the world. It's part of the Max Planck Society, the internationally renowned German research society.