6136 Individual or Team Projects
This year, I’m placing more weight on a final project for the course, an opportunity to show off what you have learned, or something that would be useful to others, or contribute to the use, usability or application of methods for categorical data analysis.
Here is a sketch of a few ideas. Feel free to propose something other, with enough detail to give me a sense of your scope & purpose. Please speak to me or, better yet, send me an email by the end of Reading Week with a brief sketch of what you want to do.
You can work on one of these individually or with one partner. I would expect something more substantial for a team project than an individual one.
Use of AI: I describe a general policy for responsible Use of AI tools in this course. Please read this and ask me questions where this is unclear in relation to what you want to do. A main requirement is that you to cite as sources any assistance you obtained from AI agents.
Recent developments in Categorical Data Analysis
Compile an overview of recent research papers illustrating interesting applications, modelling developments, graphical methods, … of categorical data analysis, attempting to go beyond what is covered in the course or my book.
Each should have a bibliographical citation, brief description, why it is interesting or novel. Perhaps with subject / content / method tags or categories. Or maybe organized by themes.
It could also be in the form of a methods review paper, with the title of this section, and sufficient text description to give an overview of this topic. Taking it further, something like this might be publishable, or certainly a nice blog post.
Tidy CDA
Categorical data simple for some purposes, but notoriously “untidy” –
table(), matrix(), array(),
xtabs(), … and many functions for analysis or graphics
accept data in a limited varieties of forms.
Chapter 2 in DDAR describes the
essential ideas for working with and manipulating catgegorical data,
largely within base-R. The vcdExtra vignette, Creating
and manipulating frequency tables gives some examples.
A tidy CDA project might propose, test and implement some extensions to the vcdExtra package, designed to reduce these problems. There is a sketch of some aspects of this in the vignette tidyCat: Tidy Methods For Categorical Data Analysis.
Extending vcdExtra and Categorical Data Analysis
More generally, a project to work on developing the vcdExtra package in other ways might be quite useful. For example, you might extend the vignettes, develop a scheme to classify the many datasets according to the types of methods (ordered factors, square tables, …) the illustrate, and so forth.
One way to think about this is: What analysis/graphics steps were hard for me, that I could make easier for others by writing a tutorial or developing new R functions?
There are some notes on this topic at Extending Categorical Data Analysis. These include:
Creating a CRAN task view for Categorical Data Analysis. These help the R community to find the packages related to different aspects of a topic, e.g., CRAN Task View: Probability Distributions, Psychometric Models and Methods, and so forth.
vcdandvcdExtradocumentation. A big part of developing software is to provide sufficient documentation, examples, tutorials, etc. to allow people to actually use what you’ve developed. It’s what I’ve tried to do for all my packages. I describe some ways you could contribute to the effort in Extending Categorical Data Analysis
Mosaic displays with ggplot2
The main software I use for mosaic displays is in vcd
and vcdExtra packages. There was also an attempt to do some
of this using ggplot2 in a ggmosaic
package, but that seems to have been abandoned by its’
maintainer.
In this regard, you might be interested in this Comparative Study of vcd::mosaic and geom_mosaic.
I have forked the ggmosaic project as friendly/ggmosaic, and
may use this as a new package, ggmosaic2. Anyone is
welcome to work on this for a course project.
Interactive apps
Years ago I developed an interactive application for mosaic displays, using perl CGI programming to run a SAS program on my server. It was nice in that it offered a number of sample datasets, some explanation of how it was done, and allowed upload of your own data.
The framework still exists, but SAS on the server has been retired. It would be nice to develop a new application using, e.g., R Shiny, https://shiny.rstudio.com/. Or, anything else – Python, D3.js, …
For a collection of apps, see Book Of Apps for Statistics Teaching. There are a couple of simple ones for categorical data.
New areas for CDA
There is a wide range of other areas in which categorical data arises, but are not treated directly in this course. Choose one or more and write a paper describing and illustrating them. Perhaps in the form of a tutorial? But that’s up to you.
Latent class analysis
LCA is a statistical method for finding subtypes of related cases (“latent classes”) from multivariate categorical data. It is often approached using Mplus, or other specific programs (Latent Gold). A web page by Maksim Rudnov, Ways to do Latent Class Analysis in R describes some R packages for this.
Confusion matrices
These arise in a variety of contexts, similar to the idea of agreement in square tables, but often with the idea of a predicted vs. actual classification. A paper by Kevin Johnson Visual Presentation of Statistical Concepts in Diagnostic Testing: The 2 x 2 Diagram sketches some ideas for 2 x 2 tables. Another paper by David Lovell et al. Taking the Confusion Out of Multinomial Confusion Matrices and Imbalanced Classes considers larger tables, where the interest is on the 2 x 2 tables for each A, B pair of categories.
Graphical models
These are an approach to multivariate data where variables are represented as nodes in a network and systems of conditional independence which can be described by undirected graphs. Course lecture slides by Steffen Lauritzen describe the basic ideas.
A too mathy book on this topic: Roberato (2017) Graphical
Models for Categorical Data
Develop this idea in some ways to make a contribution to the
practice of categorical data analysis. This might use
the igraph and ggraph packages to draw network
diagrams, combined with model fitting functions. A sketch of one
beginning is given in dayton-assoc-graph.R; output in dayton-assoc-graph.html
Sequential analysis
In clinical psychology, there is a large literature on methods for analyzing relations of dyads ([therapist, client], [husband, wife], [parent, child]) over time. Typically, behavioural interactions are recorded, and then coded by trained observers into some set of categories to identify patterns of behaviors and examine contingencies among data collected over time (Bakeman & Gottman, 1997).
Most often, such data are analyzed using simple measures of association (odds ratio, chisq) but with a moving window over time or session. For a project review some of the literature on this topic and try to propose some alternatives, either in analysis or visualization.