Blog

Notes on R, statistics and reproducible workflows.

How to Install R and RStudio (2026): Step-by-Step with Screenshots

r-basics

getting-started

Install R and RStudio on Windows, macOS or Linux in about ten minutes, then run your first lines of R: arithmetic, variables, vectors, a data frame, a histogram and your first package. Every step shown with real screenshots.

Oct 13, 2026

9 min

Building a Traceability Matrix for Statistical Programming (Without Maintaining It by Hand)

clinical

validation

r-programming

What a traceability matrix must link in a clinical programming project (SAP, specifications, programs, outputs, QC records), how to generate it from metadata in R instead of editing a spreadsheet, and how it supports a SAS-to-R equivalence report.

Oct 8, 2026

5 min

From SAS Macros to R Functions: A Worked Conversion

clinical

sas-to-r

r-programming

A SAS summary macro converted step by step into a tested R function inside a package: parameter mapping, by-group handling, missing values, formatted output and unit tests. The pattern that makes a SAS-to-R migration maintainable.

Oct 8, 2026

5 min

SAS to R Migration Roadmap: The Five Phases, What Each Delivers and What It Costs

clinical

sas-to-r

A phase-by-phase plan for moving clinical statistical programming from SAS to R: assessment, conversion, equivalence testing, documentation and sponsor/regulatory adoption. Deliverables, effort drivers and the mistakes that make migrations stall.

Oct 8, 2026

5 min

Missing Values in SAS vs R: The Differences That Change Your Numbers

sas-to-r

r-programming

clinical

SAS has numeric missing (.) and 27 special missings that sort low and compare as the smallest value; R has NA that propagates and NULL that is not a value. How each behaviour affects filters, sorts, counts and derivations in a SAS-to-R migration, with runnable examples.

Oct 8, 2026

6 min

Qualifying R Packages for Clinical Use with riskmetric and renv

clinical

validation

r-programming

A repeatable procedure for approving R packages in a regulated environment: acceptance criteria, riskmetric scoring, running package test suites as operational qualification, pinning with renv, and the decision record an auditor expects.

Oct 8, 2026

5 min

Dual Programming SAS vs R: Numerical Tolerance Rules That Survive QC

clinical

sas-to-r

validation

How to compare SAS and R outputs at dataset and TLF level during a migration: which tolerances to use for p-values, estimates and percentages, how to automate the comparison in R, and how to classify every difference as explained, accepted or deviation.

Oct 8, 2026

7 min

Why SAS and R Round Differently (and How to Make Them Agree)

clinical

sas-to-r

validation

SAS rounds half away from zero; R’s round() rounds half to even and works on binary floating point. Here is exactly where the differences appear in clinical tables, how to reproduce SAS rounding in R, and which rule to write into your tolerance document.

Oct 8, 2026

5 min

PROC FREQ, PROC MEANS and PROC UNIVARIATE in R: Side-by-Side Translations

sas-to-r

r-programming

clinical

The three SAS procedures behind most clinical summary tables, translated to base R and dplyr with matching output: frequencies and percentages with missing handling, by-group descriptive statistics, percentiles with SAS definitions, and the options that cause mismatches.

Oct 8, 2026

5 min

R vs SAS for Clinical Trials in 2026: An Honest Comparison for Decision-Makers

clinical

sas-to-r

Where R and SAS actually differ for clinical statistical programming today: regulatory acceptance, validation burden, the pharmaverse ecosystem, talent, cost, and the risks of migrating or of not migrating. Written for biostatistics heads and QA leads rather than programmers.

Oct 8, 2026

5 min

How to Write an R Validation Plan for Regulatory Submissions

clinical

validation

sas-to-r

A practical structure for validating R in a GxP clinical environment: scope and risk assessment, environment qualification with renv, package risk assessment with riskmetric, dual programming, traceability, deviation handling and the validation summary report. Templates described section by section.

Oct 8, 2026

5 min

ADaM Derivations in R with admiral: a Mini ADSL, End to End

clinical

cdisc

biostatistics

Derive an ADSL-style analysis dataset in R with the pharmaverse admiral package: treatment variables, analysis flags, age groups and time-to-event variables — every step traceable.

Aug 8, 2026

4 min

Is R Accepted by the FDA? The State of R-Based Submissions

clinical

cdisc

What the R Consortium Submissions Working Group pilots actually demonstrated, why ‘validated software’ is a property of your process rather than a licence, and what a defensible R stack looks like for CROs.

Aug 8, 2026

3 min

Clinical TLFs in R: gtsummary and rtables Side by Side

clinical

cdisc

biostatistics

Produce clinical trial tables in R two ways: a demography Table 1 with gtsummary and an adverse-event summary with rtables — the pharmaverse package built for shell-faithful CSR layouts.

Aug 8, 2026

3 min

Biostatistics datasets built into R (that you can explore in the browser)

r-tutorial

biostatistics

datasets

teaching

A guided tour of the clinical and biostatistics datasets that ship with R and its packages — infert, esoph, lung, pbc, birthwt, trial and the medicaldata collection — with what each is good for, and a browser playground to try them with no install.

Jul 10, 2026

4 min

gtsummary for beginners: build a Table 1 from clinical data, step by step

clinical

biostatistics

gtsummary

r-tutorial

A gentle, hands-on gtsummary tutorial in R. Starting from a clinical trial dataset, we build a publication-ready Table 1 one verb at a time — then you can run it yourself in the browser.

Jul 10, 2026

4 min

The Markdown cheat sheet (with a live editor)

markdown

reference

A compact Markdown syntax reference: headings, emphasis, lists, links, images, code, blockquotes and tables — with the rendered result beside each rule.

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