This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Camarda, C. G. Articles by Gampe, J. Search for Related Content Social Bookmarking                         What's this?

Modelling general patterns of digit preference

Max Planck Institute for Demographic Research, Rostock, Germany. E-mail: camarda{at}demogr.mpg.de

Paul H.C. Eilers

Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, The Netherlands. Data Theory Group, Leiden University, The Netherlands

Jutta Gampe

Max Planck Institute for Demographic Research, Rostock, Germany

In many applications data can be interpreted as indirect observations of a latent distribution. A typical example is the phenomenon known as digit preference, i.e. the tendency to round outcomes to pleasing digits. The composite link model (CLM) is a useful framework to uncover such latent distributions. Moreover, when applied to data showing digit preferences, this approach allows estimation of the proportions of counts that were transferred to neighbouring digits. As the estimating equations generally are singular or severely ill-conditioned, we impose smoothness assumptions on the latent distribution and penalize the likelihood function. To estimate the misreported proportions, we use a weighted least-squares regression with an added L₁ penalty. The optimal smoothing parameters are found by minimizing the Akaike’s information Criterion (AIC). The approach is verified by a simulation study and several applications are presented.

Key Words: composite link model digit preference • L penalty • penalized likelihood • smoothing

Statistical Modelling, Vol. 8, No. 4, 385-401 (2008)
DOI: 10.1177/1471082X0800800404


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?