Clinical & Research Statistics
- Study design & power analysis
- Bayesian & frequentist modeling
- Interim monitoring & adaptive designs
- Manuscript-ready results & interpretation
Statistical Consulting · Research Software · Education
Rigorous statistics.
Deployable software.
Research that matters.
I’m building a small consulting practice alongside my academic work. The goal: give research teams clear statistical guidance, working code, and documentation they can actually maintain.
- Practice status
- Accepting first collaborators
- Base
- Denton, TX
- Focus
- Clinical research & academic programs
Practice update
Thornton Statistical Consulting is new. I’m building the first client roster while supporting students and collaborators from my academic work.
- Role
- Assistant Professor of Statistics
- Institution
- Independent practice
- Practice
- Thornton Statistical Consulting
- Tooling
- R · Python · Stan · Next.js
Who I support
Medical research teamsClinical trial sponsorsAcademic labsHealth tech startupsPharma & biotechPublic health orgs
Services
What I actually deliver
Custom Research Software
- Data pipelines & automation
- Interactive dashboards & apps
- Statistical tooling & APIs
- Reproducible analysis frameworks
Advisory & Education
- Fractional statistical leadership
- Team training & workshops
- Grant support & methodology review
- Curriculum & course development
About
Hi, I'm Micah Thornton.
Statistician, software builder, and research advisor. I move between R/Python notebooks, registrational study plans, and production codebases without handing anything off to chance.
The job is to uncover the signal, package it so people can act on it, and leave teams with systems they can evolve. I partner directly with founders, PIs, and R&D leaders - no bloated teams, just thoughtful work and fast loops.
Principles
- Evidence over theatrics
- Software is part of the analysis
- Reproducibility by default
- Clarity for stakeholders
Tooling
RPythonStanNext.jsSupabasePostgresDuckDBAirflowAWS
Scenarios
Example ways to work together
Re-baseline a trial without restarting
Audit assumptions, rebuild the analysis plan with regulators in mind, and ship a reproducible pipeline so the team can move forward.
Replace spreadsheet handoffs with code
Pair statistical notebooks with lightweight software so results are traceable and easy to update when new data lands.
Give students a structure to follow
Document workflows, standardize templates, and coach teams so future semesters build on the work rather than restart it.
Ways to work
Pick the cadence that fits
Sprint build
3-6 weeksComplete study plan, modeling approach, or bespoke tool delivered fast.
- Statistical plan or product spec
- Interactive dashboards/notebooks
- Runbooks + live walkthrough
Fractional lead
QuarterlyHands-on leadership embedded with your team to guide studies and cross-functional decisions.
- Weekly working sessions
- Review + sign-off on analyses
- Mentorship for analysts/engineers
Advisory retainer
MonthlyAs-needed access for audits, second opinions, or roadmap support without spinning up a full engagement.
- Same-day feedback
- Lightweight artifacts
- Private channel + office hours
Portals
Where the work lives
Process
Less ceremony. More leverage.
Every engagement follows the same four-step rhythm — fast to start, rigorous in execution, clean at hand-off.
01
Scope call
30 minutes. You describe your constraints, data, and goals. I ask the hard questions. No slides, no pitch.
02
Frame
Audit what you have, surface assumptions, and choose the statistical or software approach that fits reality — not the textbook.
03
Build
Prototype quickly, lock down governance, and deliver analyses or tooling that stakeholders can trust and verify.
04
Operationalize
Hand off documentation, dashboards, and runbooks so your team extends the work without ongoing dependency.
Approach
What to expect when we work together
Plain-language communication
I summarize statistical decisions in writing so investigators, students, and administrators stay aligned.
Shared repositories
Code, docs, and data live in your systems. Everything I build is delivered with instructions you can maintain.
Constraints first
Every plan accounts for the team you have, the time you actually get, and the reviewers who will scrutinize the work.
Resources
View all →Methods briefing
Working notes on trial design, model choices, and tooling decisions.
Access resourceCapabilities deck
Upcoming one-pager with services, availability, and rates. Request a copy while it’s in draft.
Access resourceStatistical intake template
Fill-in-the-blank sheet that speeds up onboarding and keeps deliverables clear.
Access resourceWriting
Thinking out loud.
Notes on statistics, software, and research
When to use Bayesian vs. frequentist - a practical guide for clinical researchers
The choice isn't philosophical. It depends on your prior information, regulatory context, and what you’re trying to communicate.
View all articles →Building reproducible pipelines: the stack that doesn’t break in six months
Most analysis code is write-once. Here's how to build workflows your team can actually maintain and extend.
View all articles →What to put in your statistical analysis plan (and what to leave out)
An SAP that’s too vague gets you in trouble. One that’s too rigid ties your hands. Threading that needle takes practice.
View all articles →Quick brief
Prefer to keep it simple?
Send an email with a short summary and I’ll answer within two business days. No forms, no automation.
- • Who’s involved and what decision you’re trying to make
- • What data or tooling already exists
- • Deadlines, reviews, or funding constraints
What to expect
- I’ll confirm receipt and let you know if I’m the right fit.
- We’ll schedule a 30-minute working session if it makes sense.
- You get a short memo outlining options, timelines, and pricing.
FAQ
Common questions
Do you take on fractional or retainer work?+
Yes. Most partnerships blend fixed-scope builds with an ongoing cadence for questions, audits, or roadmap support.
Will you work with internal engineers or analysts?+
Absolutely. The best outcomes happen when we share the same repo, dashboards, and delivery rhythm.
What industries do you focus on?+
Primarily medical research, clinical trials, pharma, public health, and health tech — but rigorous statistics applies broadly.
What does delivery look like for software builds?+
Thin slices ship fast: spec → prototype → hardened build with docs, tests, and runbooks your team owns.
Do you teach workshops or offer student support?+
Yes. I run bespoke workshops for research teams and maintain a students portal with office hours and resources.
How do engagements typically start?+
A 30-min working session to understand your constraints, data, and goals. From there I’ll sketch a path within 48 hours.
Get in touch
Ready to work together?
Send a brief with your hypotheses, timelines, and constraints. I'll respond with a concrete path - statistical design, a custom tool, or a hybrid.
micah@thorntonstatistical.com
Calendly scheduling is reopening soon — email to coordinate a time.