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Brigham Young University - Provo

Analysis Using Smoothing Via Penalized Splines as Implemented in LME() in R

Abstract

dc:description.abstract

Spline smoothers as implemented in common mixed model software provide a familiar framework for estimating semi-parametric and non-parametric models. Following a review of literature on splines and mixed models, details for implementing mixed model splines are presented. The examples use an experiment in the health sciences to demonstrate how to use mixed models to generate the smoothers. The first example takes a simple one-group case, while the second example fits an expanded model using three groups simultaneously. The second example also demonstrates how to fit confidence bands to the three-group model. The examples use mixed model software as implemented in lme() in R. Following the examples a discussion of the method is presented.

Degree

thesis:*
Name thesis:degree_name
MS
Grantor dc:publisher
Brigham Young University - Provo

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Howell, John R.

Subjects

dc:subject × 6

Rights

Language dc:language
English

Identifiers

dc:identifier.*
Repository record dc:identifier
https://scholarsarchive.byu.edu/etd/1069
OAI identifier oai:identifier
oai:scholarsarchive.byu.edu:etd-2068

Chain of custody

source
Harvested from
Brigham Young University
Base URL
scholarsarchive.byu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Howell, John R.. Analysis Using Smoothing Via Penalized Splines as Implemented in LME() in R. Brigham Young University - Provo, https://scholarsarchive.byu.edu/etd/1069