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The Measure of Fit and Cut-Off Point for a Binomial Logit Model. an Overlooked Contribution of Jan Salomon Cramer Cover

The Measure of Fit and Cut-Off Point for a Binomial Logit Model. an Overlooked Contribution of Jan Salomon Cramer

Open Access
|Jun 2026

Abstract

Research background

This paper revisits the contribution of Jan Salomon (Mars) Cramer (1928–2014) to binomial logit modelling. Cramer proposed both a novel measure of fit for binomial logit models and a cut-off point for binary classification, particularly suitable for unbalanced samples.

Purpose

To present and demonstrate J.S. Cramer’s often-overlooked proposals for a new measure of fit and a cut-off point in binomial logit models. Additionally, the paper discusses the relevance of Cramer’s contributions in the current discourse on binomial logit modelling.

Research methodology

The study is based on a literature analysis aimed at establishing the current state of knowledge regarding J.S. Cramer’s contributions to binomial logit modelling, including the citation analysis using Scopus.

Results

We highlight that the measure of fit proposed by Cramer in 1999, known as Cramer’s lambda, has gained recognition in the literature under a different name – Tjur’s D – introduced a decade later (2009). We also note that Cramer’s proposed cut-off point, alpha, is rarely cited as an alternative to more commonly referenced thresholds. These arguments are illustrated with a numerical example.

Novelty

Both of J.S. Cramer’s proposals remain relatively unknown today. We hope this paper contributes to re-establishing Mars Cramer’s legacy in econometrics. Cramer’s lambda and Cramer’s alpha deserve recognition and adoption as legitimate standards for binomial logit modelling.

DOI: https://doi.org/10.2478/foli-2026-0004 | Journal eISSN: 1898-0198 | Journal ISSN: 1730-4237
Language: English
Page range: 70 - 86
Submitted on: May 14, 2025
Accepted on: Jan 16, 2026
Published on: Jun 29, 2026
Published by: University of Szczecin
In partnership with: Paradigm Publishing Services

© 2026 Marek Gruszczyński, published by University of Szczecin
This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 License.