Monte Carlo Confidence Intervals for the Indirect Effect with Missing Data
Ivan Jacob Agaloos Pesigan
2023-09-18
Source:vignettes/manMCMedMiss.Rmd
manMCMedMiss.Rmd
Description
Research compendium for the manuscript Pesigan, I. J. A., & Cheung, S. F. (2023). Monte Carlo confidence intervals for the indirect effect with missing data. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02114-4
Acknowledgment
The simulation was performed in part at the High-Performance
Computing Cluster (HPCC) which is supported by the Information and
Communication Technology Office (ICTO) of the University of Macau. See
https://icto.um.edu.mo/teaching-learning-research/high-performance-computing-cluster-hpcc/
for more information on the University of Macau’s High-Performance
Computing Cluster (HPCC). We used the third-generation HPCC (Coral)
particularly the serial-normal and
serial-short cluster partitions. See
.sim/README.md and the scripts in the .sim
folder in the GitHub repository
for more details on how the simulation was performed.
Installation
You can install manMCMedMiss from GitHub with:
if (!require("remotes")) install.packages("remotes")
remotes::install_github("jeksterslab/manMCMedMiss")See Containers for containerized versions of the package.
Author-Accepted Manuscript
See https://github.com/jeksterslab/manMCMedMiss/blob/main/.setup/latex/manMCMedMiss-manuscript.Rtex for the latex file of the manuscript. See https://github.com/jeksterslab/manMCMedMiss/blob/latex/manMCMedMiss-manuscript.pdf for the compiled PDF.
R Package
Monte Carlo confidence intervals for free and defined parameters in
models fitted in the structural equation modeling package
lavaan can be generated using the semmcci
package. semmcci is available on the Comprehensive R
Archive Network (CRAN) (https://CRAN.R-project.org/package=semmcci).
Documentation and examples can be found in the accompanying website (https://jeksterslab.github.io/semmcci).
More Information
See GitHub Pages for package documentation.