Documentation and Guides for fxl
This section contains a mix of various posts/guides/demonstrations/etc. that are related to drawing Single-case Design (SCD) figures using R. Generally, this is done in the interest of open science and transparency to assist in the replication of research findings. Posts in this section aren't necessarily meant to be read in order, but it probably would help to do so, since earlier content will cover more fundamental details.
This post provides some introductory content to R, with information and tips for using R for building single-case design figures. Specifically, some basic instructions and practices are provided for working with variables, functions, data types, data structures, and some common programming conventions. It is recommended to review this content to understand the types of syntax used to design figures with the fxl R package.
This post is an initial introduction to the fxl R packages and the data and practices necessary to construct single-case design figures with the package. Specifically, the types of data structure and organization necessary to use the package are covered along with a brief prototypical example. Other strategies for supporting the re-usability of written code (e.g., for common/routine practices) are also covered.
Guidance is provided for designing a treatment evaluation (research or clinical) via a Reversal Design. Annotations and other features are shown to create a script with features commensurate to those you might see in published research.
Drawing Multiple Baseline Designs in R: Communication Training across Settings
Tutorial on designing a Multiple Baseline Design figure using R. Source code and documentation for recreating figures for Gilroy et al. (2021).
This short post shows how to create one of the most commonly-used figures included in SCD research--the analogue FA based on Iwata et al. (1984/1992).
Drawing Hybrid/Blended Designs in R: Recreating Treatment Evaluation in Gilroy et al. (2019).
This tutorial shows a figure that can be necessary when there is a need to demonstrate experimental control but only two functions/targets are relevant. This figure also review conventions for visualizing schedule thinning/demand fading.
Compound Figures in R: Integrating Integrity and Behavior Rates in FA Figures
This post/guide shows how to create a figure that shows how to dynamically create figures to show information that otherwise would require two or more figures. This guide shows how to overlay a Bar Series over a Multielement chart to simultaneously communicate information about internal validity as well as the presence of some functional relationship.
This entry covers one of the more challenges issues with single-case visuals (e.g., complications from having many individuals with distinct patterns of data). This guide shows how to visualize competing selections, with changes in contexts (i.e., transitions in Phase ), with wrapping facets. Facet-specific styling is also modeled/demonstrated in this post.