Tuesday, April 2, 2019
3:30 pm - 4:30 pm
701 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104
Title: Smoothing spline mixed-effects density models for clustered dataAbstract: Smoothing spline mixed-effects density models are proposed for the nonparametric
estimation of density and conditional density functions with clustered data.
The random effects in a density model introduce within-cluster correlation and
allow us to borrow strength across clusters by shrinking cluster specific density
function to the population average, where the amount of shrinkage is decided
automatically by data. Estimation is carried out using the penalized likelihood
and computed using a Markov chain Monte Carlo stochastic approximation algorithm.
We apply our methods to investigate evolution of hemoglobin density functions
over time in response to guideline changes on anemia management for dialysis
patients.