Penalized regression, mixed effects models and appropriate modelling

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.

You are here

Penalized regression, mixed effects models and appropriate modelling

TitlePenalized regression, mixed effects models and appropriate modelling
Publication TypeJournal Article
Year of Publication2013
AuthorsHeckman, N, Lockhart, R, Nielsen, JD
JournalELECTRONIC JOURNAL OF STATISTICS
Volume7
Pagination1517-1552
Type of ArticleArticle
ISSN1935-7524
KeywordsLinear mixed effects models, P-splines, penalized smoothing, sandwich estimator
AbstractLinear mixed effects methods for the analysis of longitudinal data provide a convenient framework for modelling within-individual correlation across time. Using spline functions allows for flexible modelling of the response as a smooth function of time. A computational connection between linear mixed effects modelling and spline smoothing has resulted in use of spline functions in longitudinal data analysis and the use of mixed effects software in smoothing analyses. However, care must be taken in exploiting this connection, as resulting estimates of the underlying population mean might not track the data well and associated standard errors might not reflect the true variability in the data. We discuss these shortcomings and suggest some easy-to-compute methods to eliminate them.
DOI10.1214/13-EJS809