Streamed Longitudinal Analysis (SLA)
This is a repository for the R package to estimate mean regression parameters for longitudinal data using an online streaming procedure. The R package's main files are:
- src/increQIF_AR1.cpp: this file defines the Rcpp functions that computes the streaming updates for the mean regression parameters.
- R/SLA_func.R: this file defines the R function for the SLA estimation of model parameters.
The SLA man file contains an example for running the regression models from the paper.
Please email ehector@ncsu.edu with any questions or bug-reports.
The SLA R package can be installed in one of two ways:
- from the downloaded gzipped tarball as R CMD INSTALL SLA_1.0-1.tar.gz
- from the downloaded and renamed SLA folder as R CMD build SLA and R CMD INSTALL SLA_1.0-1.tar.gz
Please make sure to have all packages listed in the DESCRIPTION file already installed. If you encounter a library not found error for lgfortran, please try installing gfortran from here: https://cran.r-project.org/bin/macosx/tools/.
If you use the SLA R package, please consider citing the relevant manuscript: L. Luo, J. Wang and E.C. Hector (2023). Statistical inference for streamed longitudinal data. Biometrika. doi: 10.1093/biomet/asad010.
L. Luo and P. X.-K. Song (2020). Renewable estimation and incremental inference in generalized linear models withstreaming datasets. Journal of the Royal Statistical Society, Series B, 82:69–97.
A. Qu, B. G. Lindsay and B. Li (2000). Improving generalised estimating equations using quadratic inference functions. Biometrika, 87(4):823–836.
The posdef.matrix function was written by Ravi Varadhan: https://stat.ethz.ch/pipermail/r-help/2008-February/153708.