A Study on Reproducibility and the Reliability of the Hosmer-Lemeshow Test in Published Research

This paper discusses two elements of reproducibility in published research. First, it examines whether published results are reproducible with author-supplied data: specifically, whether the authors publish their data, whether authors respond to requests for data when data are claimed to be available upon reasonable request, and whether data provided are usable to reproduce the authors’ results. Second, we seek to substantiate the currently mostly theoretical concerns about the Hosmer-Lemeshow goodness-of-fit test’s lack of power by investigating its usage in practice: in published research, by authors aiming to validate their models. By using the authors’ data to build larger alternative models and doing hypothesis testing to show that the smaller models—validated by Hosmer-Lemeshow—do not adequately capture information that is available in the data, we demonstrate that the Hosmer-Lemeshow goodness of fit test is often incapable of detecting inadequacies in models.

Authors

Publication Details

Journal
The New England Journal of Statistics in Data Science
Published
2025-01-01
DOI
https://doi.org/10.51387/25-nejsds81
Citations
1
Primary Topic
Meta-analysis and systematic reviews
Type
article
Field-Weighted Citation Impact
1.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on Reproducibility and the Reliability of the Hosmer-Lemeshow Test in Published Research

Airu Yang, Kun Yang
1 citations
The New England Journal of Statistics in Data Science
Meta-analysis and systematic reviews
1.40
article

A Study on Reproducibility and the Reliability of the Hosmer-Lemeshow Test in Published Research

Airu Yang, Kun Yang
article en
1 citations

Abstract

This paper discusses two elements of reproducibility in published research. First, it examines whether published results are reproducible with author-supplied data: specifically, whether the authors publish their data, whether authors respond to requests for data when data are claimed to be available upon reasonable request, and whether data provided are usable to reproduce the authors’ results. Second, we seek to substantiate the currently mostly theoretical concerns about the Hosmer-Lemeshow goodness-of-fit test’s lack of power by investigating its usage in practice: in published research, by authors aiming to validate their models. By using the authors’ data to build larger alternative models and doing hypothesis testing to show that the smaller models—validated by Hosmer-Lemeshow—do not adequately capture information that is available in the data, we demonstrate that the Hosmer-Lemeshow goodness of fit test is often incapable of detecting inadequacies in models.

The New England Journal of Statistics in Data Science
Openalex Percentile: Top 18%
Meta-analysis and systematic reviews
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.