/biostat840-project3-pkgdown-neljasonhaw

biostat840-project3-pkgdown-neljasonhaw created by GitHub Classroom

Primary LanguageROtherNOASSERTION

nlme

Linear and Nonlinear Fixed Effects Models with a new vignette by Nel Jason Haw

Description: Linear and Nonlinear Fixed Effects Models and everything you can do with them

Original Authors: Jose C. Pinheiro and Douglas M. Bates (1997-2005), R Core Team (2005-2022)

Location of Original Package

https://github.com/cran/nlme

Location of Deployed Package Website

https://jhu-statprogramming-fall-2022.github.io/biostat840-project3-pkgdown-neljasonhaw

Customizations to pkgdown website

  • Applied "simplex" bootswatch
  • Changed base font to "Source Sans Pro"
  • Changed code font to "Source Code Pro"
  • Changed theme to "github-light"
  • Changed navigation bar background to "light"

Installation

remotes::install_github(repo = "jhu-statprogramming-fall-2022/biostat840-project3-pkgdown-neljasonhaw")

List of Exported Functions (Used in New Vignette)

Descriptions provided in R Documentation

  • lme: Linear Mixed-Effects Models: This generic function fits a linear mixed-effects model in the formulation described in Laird and Wre (1982) but allowing for nested random effects. The within-group errors are allowed to be correlated and/or have unequal variances
  • anova.lme: Compare Likelihoods of Fitted Objects: Likelihood ratio test for two lme model objects

Example

This is a basic example which shows you how to solve a common problem (from lme R Documentation):

fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
anova(fm1)
fm2 <- update(fm1, random = pdDiag(~age))
anova(fm1, fm2)