Latent Class Trajectory Modelling Tools: an R Package
Maintainer: Hannah Lennon
Contact: lennonh@iarc.fr
Last Updated: August 2019
To install the R package, in the R console use the command
install.packages("devtools")
devtools::install_github("hlennon/LCTMtools")
All statistical (R and SAS) codes used to implement Latent Class Trajectory Modelling and the tools described in the manuscript "A framework to construct and interpret Latent Class Trajectory Modelling", are available here and can be downloaded from www.github.com/hlennon/LCTMtools.
An example (simulated) dataset 'bmi' and 'bmi_long' (long format version) is provided to describe the steps throughout.
Lennon H, Kelly S, Sperrin M, et al., Framework to construct and interpret Latent Class Trajectory Modelling, BMJ Open 2018;8:e020683.
Available at https://bmjopen.bmj.com/content/8/7/e020683
Supplementary material contains extra details: https://bmjopen.bmj.com/content/bmjopen/8/7/e020683/DC1/embed/inline-supplementary-material-1.pdf?download=true
There are two help manuals available above:
-
- The standard R manual detailing the input and outputs of each of the functions, called LCTMtools.pdf
https://github.com/hlennon/LCTMtools/blob/master/vignettes/LCTMtools.pdf
- The standard R manual detailing the input and outputs of each of the functions, called LCTMtools.pdf
-
- A vignette with a guided example, named LCTMtools-vignette http://rpubs.com/hlennon/LCTMtoolsvignette or https://github.com/hlennon/LCTMtools/blob/master/vignettes/LCTMtoolsvignette.pdf
library(LCTMtools)
data(bmi_long, package = "LCTMtools" )
# Use the hlme function from the 'lcmm' R package to fit a 2 class latent class trajectory model
set.seed(100)
library(lcmm)
model2classes <- lcmm::hlme(fixed = bmi ~ age + I(age^2),
mixture= ~ age,
random = ~ age,
ng = 2,
nwg = TRUE,
subject = "id",
data = data.frame(bmi_long[1:500, ]) )
# Compute model adequacy measures
LCTMtoolkit(model2classes)
# Compare with a 3 class model
set.seed(100)
model3classes <- lcmm::hlme(fixed = bmi ~ age + I(age^2),
mixture= ~ age,
random = ~ age,
ng = 3,
nwg = TRUE,
subject = "id",
data = data.frame(bmi_long[1:500, ]) )
LCTMtoolkit(model3classes)
LCTMcompare(model2classes, model3classes)
Please cite as
Hannah Lennon. {LCTMtools}: Latent Class Trajectory Models tools R Functions. R package version 0.1.2.
Lennon H, Kelly S, Sperrin M, et al Framework to construct and interpret Latent Class Trajectory Modelling BMJ Open 2018;8:e020683. doi: 10.1136/bmjopen-2017-020683
A special thank you to Charlotte Watson for testing.
I’m happy to receive bug reports, suggestions, questions, and (most of all) contributions to fix problems and add features. I prefer you use the Github issues system over trying to reach out to me in other ways. Pull requests for contributions are encouraged.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.