Clustering Longitudinal Categorical Data

Note: This is a mirror of the project with sensitive data removed. As such not all the code is represented in the commit history.

This shiny app is designed as a tool for comparing methods for clustering longitudinal categorical data. It supports doing cluster analysis on such data using a variety of appropriate clustering methods. For each method, it produces visualizations and statistics to help interpret the clustering assignments. We also allow for comparing different clusterings and producing clustering comparison statistics such as the adjusted Rand index. We include two data sets, but users could upload and analyze datasets of their choosing.

Getting Started

A pared down version of our project can be found on our shinyapps.io page. The full version should be run locally due to the computational complexity of performing clusterings.

Prerequisites

You'll need a copy of R and RStudio in order to run the app locally.

Additionally, you'll need several R packages, which can be installed by inputting the following into the RStudio console:

install.packages(c("abind",
                   "cluster",
                   "data.table",
                   "dendextend",
                   "dplyr",
                   "ggplot2",
                   "htmlTable",
                   "igraph",
                   "markdown",
                   "partitionComparison",
                   "purrr",
                   "rmarkdown",
                   "scales",
                   "seqHMM",
                   "seriation",
                   "shiny",
                   "shinybusy",
                   "shinydashboard",
                   "shinyMatrix",
                   "stringr",
                   "tidyr",
                   "TraMineR",
                   "viridis",
                   "RColorBrewer"))

install.packages("devtools")
devtools::install_github("cran/bayesMCClust")

Running the app

Open ShinyApp/shiny_prototype in RStudio, then press Run App in the upper left hand corner. A window with the app running in it should pop up.

Authors

• Dr. Brianna Heggeseth
• Ellen Graham
• Zuofu Huang
• Kieu-Giang Nguyen