Software

I build R and Shiny tools for the unglamorous middle of applied research: documenting, cleaning, linking, and reporting on administrative data.

Nebraska Suicide Mortality Review Reporting Application

Lead developer, R / Shiny · 2026–present

Application supporting Nebraska’s veteran suicide mortality review process: integrates and reconciles successive Nebraska Violent Death Reporting System (NEVDRS) exports, detects and tracks record-level changes between exports, supports structured case annotation, and generates both individual case reports and the annual report to the Legislature. Internal; not publicly released.

Internal tool; not publicly available.

NSWERS Data Explorer & Pipeline Visualization

Author, R / Shiny · 2025–present

Internal application for the Nebraska Statewide Workforce and Educational Reporting System data warehouse: locates which tables hold which variables, retrieves definitions, and traces data lineage back to the queries and source tables each variable depends on. Improves pipeline transparency, makes problems easier to pinpoint, and shortens onboarding for the team. Not publicly released.

Internal tool; not publicly available.

Recode Studio

Author & maintainer, R / Shiny · Ongoing

Dataset-agnostic R/Shiny app for cleaning messy string variables without hand-writing R: browse values, flag likely typos via spellcheck, build and preview recode rules, and export both a reusable rule set and runnable R code. Open source: github.com/amelia-m/recode-studio

Source on GitHub

Table Relationship Explorer

Author & maintainer, R / Shiny · Ongoing

Interactive tool for discovering and visualizing primary/foreign-key relationships across tabular data: multi-signal key inference with confidence scoring, interactive entity-relationship diagrams, and exportable reports across many file and database formats (with a Python/Streamlit port). Open source: github.com/amelia-m/table-explorer

Source on GitHub

Tools I use

  • Statistical & Psychometric: R Statistical Software (tidyverse; lavaan and related psychometric packages; MplusAutomation and semPlot for SEM workflows); Mplus; SAS; SPSS (including PROCESS macro); MATLAB; Jamovi; JASP
  • Synthetic Data Generation & Evaluation: tidysynthesis; syntheval (R packages, Urban Institute)
  • Data Collection: Qualtrics; REDCap; LabVIEW (data collection, signal processing, and analysis); Biopac (EMG/MMG data collection)
  • Data Management & Databases: dbplyr (R); SQL; Microsoft Access
  • Visualization & Interactive Applications: ggplot2 (R); gt (R); Shiny (R); Veusz
  • Reproducible Reporting & Publishing: Quarto (course websites, slide decks, parameterized reports, this CV); R Markdown / knitr; Markdown; LaTeX / TinyTeX
  • Research Workflow & Reference Management: targets (R package for reproducible pipelines); renv; Zotero; Obsidian; Open Science Framework (OSF)
  • Programming & Version Control: Git (GitHub, GitLab); Python (basic & LLM-assisted); Unix / Bash
  • Development Environments & Editors: Positron; RStudio; Visual Studio Code; Notepad++
  • LLM-Assisted Development: Claude Code; Gemini / Gemini CLI; GitHub Copilot; Antigravity IDE; Cursor
  • Productivity & Collaboration: Microsoft Office Suite (Excel, PowerPoint, Word, Teams, SharePoint); Adobe Acrobat Pro DC; Adobe Illustrator

More code: GitHub · GitLab · UNL GitLab