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; 4 of the 4 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

4 of 4 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

Show all 4 references

Research works printed but not linked: 53

  1. 10.2307/2531154 · DOI · Paper page
  2. 10.1093/biomet/67.1.145 · DOI · Paper page
  3. 10.2307/2530289 · DOI
  4. Kay R., 1984, Goodness of fit methods for the proportional hazards regression model: A review, Revue d'Epidémiologie et Santé Publique, 32, 185
  5. 10.2307/2531400 · DOI
  6. Schumacher M., 1984, On a goodness‐of‐fit test for the proportional hazards model, EDV in Medizin und Biologie, 15, 19
  7. 10.2307/2531155 · DOI
  8. Wei L. J., 1984, Testing goodness of fit for proportional hazards model with censored observations, Journal of the American Statistical Association, 79, 649, 10.1080/01621459.1984.10478092 · DOI
  9. 10.2307/2347465 · DOI
  10. 10.2307/2531284 · DOI
  11. 10.1093/biomet/73.2.513 · DOI
  12. Harrell F. E., 1986, SUGI Supplemental Library User's Guide, Version 5
  13. 10.1093/biomet/74.2.289 · DOI · Paper page
  14. 10.2307/2532040 · DOI
  15. Lin D. Y., 1991, Goodness‐of‐fit analysis for the Cox regression model based on a class proportional hazards model, Journal of the American Statistical Association, 86, 725, 10.1080/01621459.1991.10475101 · DOI
  16. 10.1080/01621459.1992.10475197 · DOI
  17. 10.1002/bimj.4710340505 · doi:10.1002/bimj.4710340505
  18. 10.2307/2532779 · DOI
  19. 10.2307/2288262 · doi:10.2307/2288262
  20. 10.2307/2348023 · DOI
  21. 10.2307/2347520 · DOI
  22. 10.1080/01621459.1988.10478588 · DOI
  23. Breslow N., 1972, Discussion on ‘Regression models and life tables’ by D. R. Cox, Journal of the Royal Statistical Society, Series B, 34, 216
  24. Breslow N., 1984, Methodologies for the Collection and Analysis of Mortality Data, 367
  25. Kalbfleisch J. D., 1980, The Statistical Analysis of Failure Time Data, 86
  26. 10.2307/2530904 · DOI
  27. 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).
  28. Kalbfleisch J. D., 1980, The Statistical Analysis of Failure Time Data, 15
  29. 10.2307/1402730 · DOI
  30. 10.3109/07357909009017550 · doi:10.3109/07357909009017550
  31. 10.3109/07357908309020278 · doi:10.3109/07357908309020278
  32. 10.2307/1403046 · doi:10.2307/1403046
  33. 10.1093/biomet/76.4.763 · DOI
  34. Kalbfleisch J. D., 1980, The Statistical Analysis of Failure Time Data, 214
  35. 10.2307/2347073 · DOI
  36. 10.2307/2532499 · DOI
  37. O'Quigley J., 1984, Testing the proportional hazards regression model against some general alternatives, Revue d' Épidémiologie et Santé Publique, 3, 199
  38. 10.2307/2347444 · DOI
  39. Simon R., 1984, Cancer Clinical Trials – Methods and Practice, 444
  40. 10.2307/2531633 · DOI
  41. 10.2307/2532096 · DOI
  42. Kalbfleisch J. D., 1980, The Statistical Analysis of Failure Time Data, 134
  43. 10.1016/0197-2456(81)90005-2 · DOI
  44. 10.1080/01621459.1992.10476248 · DOI · Paper page
  45. 10.1002/sim.4780131007 · DOI · Paper page
  46. 10.2307/2347382 · DOI
  47. 10.1080/01621459.1979.10481038 · DOI · Paper page
  48. Hastie T., 1990, Generalized Additive Models, 9
  49. 10.2307/2556114 · DOI
  50. 10.2307/2348379 · DOI
  51. Hastie T., 1993, Varying‐coefficient models, Journal of the Royal Statistical Society, Series B, 55, 757, 10.1111/j.2517-6161.1993.tb01939.x · DOI · Paper page
  52. 10.1093/biomet/80.3.557 · DOI · Paper page
  53. 10.1093/biomet/77.1.147 · DOI · Paper page

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
4
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Graphical methods for assessing violations of the proportional hazards assumption in cox regression. https://app.cochat.ai/papers/10.1002/sim.4780141510
The paper
Hess, K. R. (1995). Graphical methods for assessing violations of the proportional hazards assumption in cox regression. Statistics in Medicine. https://doi.org/10.1002/sim.4780141510

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.