Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 549

The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.

Graphical methods for assessing violations of the proportional hazards assumption in cox regression

Hess, Kenneth R.·1995·Statistics in Medicine
DOI 10.1002/sim.4780141510
Open this paper in CoChat — free account

Abstract

A major assumption of the Cox proportional hazards model is that the effect of a given covariate does not change over time. If this assumption is violated, the simple Cox model is invalid, and more sophisticated analyses are required. This paper describes eight graphical methods for detecting violations of the proportional hazards assumption and demonstrates each on three published datasets with a single binary covariate. I discuss the relative merits of these methods. Smoothed plots of the scaled Schoenfeld residuals are recommended for assessing PH violations because they provide precise usable information about the time dependence of the covariate effects.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/sim.4780141510

Cites

45 of 45 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 14

  1. Kay R., 1984, Goodness of fit methods for the proportional hazards regression model: A review, Revue d'Epidémiologie et Santé Publique, 32, 185
  2. Schumacher M., 1984, On a goodness‐of‐fit test for the proportional hazards model, EDV in Medizin und Biologie, 15, 19
  3. Harrell F. E., 1986, SUGI Supplemental Library User's Guide, Version 5
  4. 10.1002/bimj.4710340505 · doi:10.1002/bimj.4710340505
  5. 10.2307/2288262 · doi:10.2307/2288262
  6. Breslow N., 1972, Discussion on ‘Regression models and life tables’ by D. R. Cox, Journal of the Royal Statistical Society, Series B, 34, 216
  7. Breslow N., 1984, Methodologies for the Collection and Analysis of Mortality Data, 367
  8. Harrell F. E.andLee K. L.‘Verifying assumptions of the Cox proportional hazards model’ SUGI II: Proceedings of the Eleventh Annual SAS Users Group International Conference 823–828(1986).
  9. 10.3109/07357909009017550 · doi:10.3109/07357909009017550
  10. 10.3109/07357908309020278 · doi:10.3109/07357908309020278
  11. 10.2307/1403046 · doi:10.2307/1403046
  12. Kalbfleisch J. D., 1980, The Statistical Analysis of Failure Time Data, 214
  13. O'Quigley J., 1984, Testing the proportional hazards regression model against some general alternatives, Revue d' Épidémiologie et Santé Publique, 3, 199
  14. Kalbfleisch J. D., 1980, The Statistical Analysis of Failure Time Data, 134

Cited by

See all 549

Metadata

Authors
Hess, K. R.
Venue
Statistics in Medicine
Publisher
Wiley
Published
1995-08-15
Volume
14
Issue
15
Pages
1707-1723
ISSN
  • 0277-6715 (ISSN-L)
  • 1097-0258
DOI
10.1002/sim.4780141510
OpenAlex
W2053452241
Cited by
549
References
45
FWCI
5.21
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor, 4215 d)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.