Survival Analysis in Excel with BESHStatNG: Kaplan–Meier, Log-rank, and Cox Regression

If you work with time-to-event data (clinical outcomes, reliability, churn/retention, follow-up studies), you already know the pain: survival analysis is powerful, but many workflows pull you out of Excel and into a separate stats stack.

BESHStatNG brings survival analysis directly into Excel—so you can prepare data, run analyses, and generate publication-ready outputs where your team already works. Continue reading “Survival Analysis in Excel with BESHStatNG: Kaplan–Meier, Log-rank, and Cox Regression”

BESHStatNG v0.4.0: Publication-ready Chart Export + Animated 3D XYZ Scatterplot GIFs

The latest BESHStatNG release (v0.4.0) adds two highly requested features:
(1) a dedicated Chart Export dialog for publication-quality figures, and
(2) an Animated GIF workflow for the 3D XYZ scatterplot.
Both features work directly inside Excel and do not require installing external tools or scripting environments. Continue reading “BESHStatNG v0.4.0: Publication-ready Chart Export + Animated 3D XYZ Scatterplot GIFs”

BESHStatNG Update v0.3.2: New Agreement Module for Method Comparison & Reliability

A new version of BESHStatNG is now available, and it introduces a major addition: the new Agreement module. This release is focused on method comparison and reliability workflows commonly used in laboratory medicine, medical research, and quality assessment. Continue reading “BESHStatNG Update v0.3.2: New Agreement Module for Method Comparison & Reliability”

BESHstatNG v0.3.0 released — spotlight on GLM, NB2, and Zero-Inflated Poisson

The first official release of BESHstatNG (v0.3.0) is now available — an open-source Excel add-in (Excel-DNA + VB.NET, installed via MSI) that continues the original VBA-based BESHstat tradition with very similar coverage of statistical tests and methods, now on a modern and maintainable foundation.

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Nonparametric methods in BESHStatNG: exact p-values (even with ties) at Excel speed

If you do statistics in Excel, nonparametric tests are often the difference between “I can analyze this now” and “I need to export to another tool.” BESHStatNG keeps the workflow Excel-first, while providing a compiled engine and robust implementations of the methods people use most.

This post is a quick update on what’s already implemented — with a special focus on exact p-value computation with tie handling, computed fast via dynamic programming. Continue reading “Nonparametric methods in BESHStatNG: exact p-values (even with ties) at Excel speed”

BESHStatNG is happening: a modern VB.NET re-implementation of the classic BESHStat Excel add-in

If you’ve used the original BESHStat (VBA / .xlam) add-in over the years, you already know the idea: keep statistics close to the spreadsheet and make analysis fast and practical.

Now I’m rebuilding it as BESHStatNG (New Generation) — a VB.NET + Excel-DNA add-in distributed as a lightweight .xll. Continue reading “BESHStatNG is happening: a modern VB.NET re-implementation of the classic BESHStat Excel add-in”

Multiple Correspondence Analysis (CA) in Excel

Multiple Correspondence Analysis (MCA) is an exploratory multivariate technique designed to analyze and visualize relationships among several categorical variables. It can be seen as the extension of Correspondence Analysis (CA), which is limited to two categorical variables, to the case of more than two variables. Continue reading “Multiple Correspondence Analysis (CA) in Excel”

Correspondence Analysis (CA) in Excel

Correspondence Analysis (CA) is an exploratory multivariate statistical technique designed to analyze and visualize relationships in categorical data. It is most often applied to contingency tables—tables that cross-classify observations into categories—making it particularly useful for survey data, market research, linguistics, ecology, and the social sciences. Continue reading “Correspondence Analysis (CA) in Excel”

Generalized Estimating Equations (GEE) in Excel

Generalized Estimating Equations (GEE) are a method for analyzing correlated response data, such as repeated measurements on the same subject or observations clustered within groups. GEE extends the framework of Generalized Linear Models (GLMs) to situations where the assumption of independence between observations is not appropriate. Continue reading “Generalized Estimating Equations (GEE) in Excel”