**CR2**: Compute CR0, CR1, CR2 cluster robust standard errors with empirical-degrees of freedom adjustments. (July 2022).

This is now on CRAN so can be installed using: `install.packages('CR2')`

. The development version can also be installed using: `devtools::install_github("flh3/CR2")`

.

The SPSS version is available here.

For more details:

Huang, F. & Li, X. (2022). Using cluster robust standard errors when analyzing group randomized trials with few clusters. *Behavior Research Methods*, 54, 1181-1199. doi: 10.3758/s13428-021-01627-0

Huang, F., Wiedermann, W., & Zhang, B. (2022). Accounting for heteroskedasticity resulting from between-group differences in multilevel models. *Multivariate Behavioral Research.* doi: 10.^{1080}⁄_{00273171}.2022.2077290.

Huang, F., Zhang, B., & Li, X. (2022). Using robust standard errors for the analysis of binary outcomes with a small number of clusters. *Journal of Research on Educational Effectiveness.* https://doi.org/10.1080/19345747.2022.2100301

**MLMusingR**: Companion package to “*Practical Multilevel Modeling Using R”* (forthcoming, 2023). (July 2022).

**gendata**: Generate and modify synthetic datasets. Create synthetic datasets based on a correlation table. Additional functions can be used to rescale, transform, and reverse code variables.
DOC

**hornpa**: A stand-alone function that generates a user specified number of random datasets and computes eigenvalues using the random datasets (i.e., implements Horn’s [1965, Psychometrika] parallel analysis).
DOC

# Shiny

Testing out Shiny– a web application framework for R.

Conduct a parallel analysis online to determine the number of components/factors to retain. No need to download any syntax files or packages. *NOTE: For some reason, the EFA PA is not working properly* (but it does in the package).

# Conducting multilevel CFA in R

I wrote a short note a while back (which I’ve kept updating) on conducting a multilevel confirmatory factor analysis using R (with *lavaan*). The note and the directions on using the function can be found using this link. NOTE: the updated version of *lavaan* now has a feature that automates the cumbersome multilevel setup. Additional notes can be found here.

Please cite as:

Huang, F. (2017). *Conducting multilevel confirmatory factor analysis using R*. doi: 10.13140/RG.2.2.12391.34724. Retrieved from https://francish.netlify.app/docs/MCFAinRHUANG.pdf

You can access the function at this link on https://github.com/flh3/mcfa.