reviewBMC Medical Research MethodologyMar 6, 2019GOLD OA

A review of spline function procedures in R

University of Essex · University of Freiburg · +3 more institutions

PubMed
Indexed incrossrefdatacitedoajpubmed

Abstract

Background

With progress on both the theoretical and the computational fronts the use of spline modelling has become an established tool in statistical regression analysis. An important issue in spline modelling is the availability of user friendly, well documented software packages. Following the idea of the STRengthening Analytical Thinking for Observational Studies initiative to provide users with guidance documents on the application of statistical methods in observational research, the aim of this article is to provide an overview of the most widely used spline-based techniques and their implementation in R.

Methods

In this work, we focus on the R Language for Statistical Computing which has become a hugely popular statistics software. We identified a set of packages that include functions for spline modelling within a regression framework. Using simulated and real data we provide an introduction to spline modelling and an overview of the most popular spline functions.

Citation impact

569
total citations
FWCI
31.50
Percentile
100%
References
42
Citations per year

Authors

4

Topics & keywords

Keywords
  • Univariate
  • Computer science
  • Spline (mechanical)
  • Observational study
  • Software
  • Data science
  • Regression analysis
  • Machine learning
No related works found for this paper.