Journal
BIOMETRIKA
Volume 89, Issue 1, Pages 111-128Publisher
BIOMETRIKA TRUST
DOI: 10.1093/biomet/89.1.111
Keywords
basis function; confidence band; hypothesis testing; least squares; longitudinal data; polynomial spline; resampling subject bootstrap; varying-coefficient model
Ask authors/readers for more resources
A global smoothing procedure is developed using basis function approximations for estimating the parameters of a varying-coefficient model with repeated measurements. Inference procedures based on a resampling subject bootstrap are proposed to construct confidence regions and to perform hypothesis testing. Conditional biases and variances of our estimators and their asymptotic consistency are developed explicitly. Finite sample properties of our procedures are investigated through a simulation study. Application of the proposed approach is demonstrated through an example in epidemiology. In contrast to the existing methods, this approach applies whether or not the covariates are time-invariant and does not require binning of the data when observations are sparse at distinct observation times.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available