A comprehensive R package with 15 analysis modules — from descriptive stats to SEM, bibliometrics, and fsQCA — with free AI-powered result interpretation.
Dr.AIStat runs inside RStudio — a free, beginner-friendly app. Follow these 4 steps and you'll be analysing data in minutes.
R is the free statistical engine that powers Dr.AIStat. Download the latest version for Windows, Mac, or Linux.
Download R (Free)RStudio is the free visual interface for R. It's like Microsoft Word — but for statistics. Very easy to use.
Download RStudio (Free)Open RStudio, click the Console panel at the bottom, paste the install command, and press Enter.
See Install Command ↓Type run_draiststat() in the Console and press Enter. The app opens in your browser automatically.
Open RStudio → find the Console panel (bottom-left) → paste each command below one at a time → press Enter after each one and wait for it to finish before moving to the next.
▶ STEP 1 — Run this once (only needed the first time):
install.packages("devtools")
▶ STEP 2 — Install Dr.AIStat (wait for it to finish — may take 1–2 min):
# Official DrAIStudio repository details will be listed here when public package access is finalized.
▶ STEP 3 — Launch the app (do this every time you want to use it):
run_draiststat()
✅ The app opens in your browser automatically · All analyses run locally · No subscription, no data uploads
💡 Already installed? Next time just open RStudio and run run_draiststat() — that's all you need.
Everything a quantitative researcher needs in one tool
psych::describe, correlations, Harman CMB test, distributions, missing data
EFA, CFA (lavaan), Cronbach's α, McDonald's ω, AVE, CR, HTMT, discriminant validity
t-test, Mann-Whitney, ANOVA, Kruskal-Wallis, MANOVA, chi-square, post-hoc tests
Simple, multiple, hierarchical OLS, standardised β, VIF, ΔR², full diagnostics
Decision Tree, Random Forest, SVM, AUC-ROC, confusion matrix, feature importance
K-Means (elbow method), Hierarchical (dendrogram), Gaussian Mixture Models (mclust)
Rasch 1PL (eRm), 2PL (ltm), item fit statistics, person-item map, reliability
Durbin-Wu-Hausman test, 2SLS instrumental variables (AER), Sargan-Hansen test
Bayesian regression (rstanarm), correlation network analysis (igraph), NCA
CB-SEM and PLS-SEM (seminr / SmartPLS-equivalent), CFA, full SEM, modification indices
Conditional Mediation Models A–E, Bootstrap CI, CoMe Index (ω), Cheah et al. (2021)
Publication trends, co-authorship, co-citation, keyword co-occurrence, thematic mapping
Calibration, truth table, necessary & sufficient conditions, parsimonious / intermediate solutions
Panel data (plm), survival analysis, regression discontinuity, ARIMA, VAR models
AI-powered result interpretation, hypothesis generation, APA writing — powered by free Groq API
Dr.AIStat uses Groq's free llama-3.1-8b-instant model to interpret your statistical results in plain English and APA format.
Visit console.groq.com/keys and sign up free
Copy your API key (starts with gsk_)
Paste it in the Dr.AIStat sidebar — done!
Independent academic AI workspace
Dr.AIStat was built to make rigorous statistical analysis accessible to every researcher — regardless of their coding background. All 15 modules are built on peer-reviewed R packages and produce APA-ready output.
📧 [email protected]Everything you need to know before you start
@software{DrAIStudio2026DrAIStat,
author = {DrAIStudio},
title = {{DrAIStat}: {AI}-Powered Statistical Analysis Tool for Research},
year = {2026},
version = {3.0.0},
url = {https://draistudio.com/stat/},
note = {R package}
}
Working paper (SSRN): Inam, A. (2026). Dr. AIStat: An AI-powered R Shiny application for integrated bibliometric and statistical analysis. SSRN. https://ssrn.com/abstract=6841458