Growth curve models
Used here; made using R Studio, packages nlme, MuMIn, and lme4. GCMs are multi-level models assessing change over time both within individuals and groups.
Multiple correspondence analysis
Used here. Method developed by Bourdieu for mapping social fields; useful for categorical variables. Made with R Studio, packages FactoMineR and factoextra. Can also be done with mvmca in Stata.
Bipartite network graphs
Used here. Made with R Studio, using igraph. See D’Esposito et al for difference between network graphs and MCA, and where each can be useful.
Computational text analysis
In preparation. Done in R Studio, using text2vec. stm is also great for doing topic modeling in social science.
In preparation. I’m playing around with doing this in python, but this free website is a really great start.
Structural equation models
Under review. Made in Stata. In other work (also under review), I have also used generalized structural equation models.