visual-analysis

Name: visual-analysis
Availability: InStock
Author: ccashwell

Apply structured visual analysis to graphed single-subject data for treatment effects.

Updated Apr 11, 2026

Search Tags:#visual-analysis #trend-analysis #data-interpretation #aba #single-subject #within-between

Ready to run

npx skills add https://github.com/ccashwell/agentic-behavior-analysis --skill visual-analysis-ccashwell

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: visual-analysis
Source: https://github.com/ccashwell/agentic-behavior-analysis/tree/main/skills/visual-analysis
Command: npx skills add https://github.com/ccashwell/agentic-behavior-analysis --skill visual-analysis-ccashwell

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visual analysis provides a rigorous, structured method to interpret graphed single-subject data, reducing guesswork in determining treatment effects.

Core Features & Use Cases

Within-Condition Analysis: level, trend, and variability evaluation within each phase to characterize data.
Between-Condition Analysis: immediacy, overlap, and replication assessment across phases to infer treatment effects.
Use Case: clinicians evaluating FA-based interventions or DTT programs to decide whether a change in phase produced clinically meaningful behavior change.

Quick Start

Apply the visual analysis framework to your graphed single-subject data to determine treatment effects.

Frequently Asked Questions about visual-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I conduct visual analysis for single-subject ABA data?▼

Visual analysis for single-subject ABA data applies a criteria-based framework evaluating within-condition features like level, trend, and variability, alongside between-condition comparisons of immediacy, overlap, and consistency to determine treatment effects.

What is the difference between within-condition and between-condition analysis in single-subject designs?▼

Within-condition analysis in single-subject designs evaluates level, trend, and variability inside a single phase, while between-condition analysis compares immediacy, overlap, and replication across different phases to infer clinically meaningful behavior change.

How do I evaluate treatment effects during a withdrawal phase in ABA?▼

To evaluate treatment effects during a withdrawal phase, apply structured visual analysis to graphed single-subject data, comparing immediacy and overlap across baseline, intervention, and replication phases to confirm whether behavior change is consistent.

Can I use structured visual analysis for DTT program data?▼

Yes, structured visual analysis works for DTT programs and FA-based interventions, applying criteria-based within-condition and between-condition assessments to single-subject graphs to guide clinical decision-making regarding phase changes.

What features should I look for when interpreting single-subject graphed data?▼

When interpreting single-subject graphed data, look for within-condition features of level, trend, and variability, and evaluate between-condition immediacy, overlap, and consistency to ensure rigorous and consistent interpretation of treatment effects.