The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Tests of calibration and goodness‐of‐fit in the survival setting
Open accessAbstract
To access the calibration of a predictive model in a survival analysis setting, several authors have extended the Hosmer–Lemeshow goodness‐of‐fit test to survival data. Grønnesby and Borgan developed a test under the proportional hazards assumption, and Nam and D'Agostino developed a nonparametric test that is applicable in a more general survival setting for data with limited censoring. We analyze the performance of the two tests and show that the Grønnesby–Borgan test attains appropriate size in a variety of settings, whereas the Nam‐D'Agostino method has a higher than nominal Type 1 error when there is more than trivial censoring. Both tests are sensitive to small cell sizes. We develop a modification of the Nam‐D'Agostino test to allow for higher censoring rates. We show that this modified Nam‐D'Agostino test has appropriate control of Type 1 error and comparable power to the Grønnesby–Borgan test and is applicable to settings other than proportional hazards. We also discuss the application to small cell sizes. Copyright © 2015 John Wiley & Sons, Ltd.
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Cited by
Yeh, R. W., Secemsky, E. A., Kereiakes, D. J., Normand, S.-L. T., Gershlick, A. H., Cohen, D. J., Spertus, J. A., Steg, P. G., Cutlip, D. E., Rinaldi, M. J., et al. (2016) · JAMA · doi:10.1001/jama.2016.3775 · Cited by 934
A tutorial on calibration measurements and calibration models for clinical prediction models
Huang, Y., Li, W., Macheret, F., Gabriel, R. A., & Ohno-Machado, L. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocz228 · Cited by 486
ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation
Khurshid, S., Friedman, S., Reeder, C., Di Achille, P., Diamant, N., Singh, P., Harrington, L. X., Wang, X., Al-Alusi, M. A., Sarma, G., et al. (2022) · Circulation · doi:10.1161/circulationaha.121.057480 · Cited by 322
Zwanenburg, A. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04391-8 · Cited by 306
Basu, S., Sussman, J. B., Berkowitz, S. A., Hayward, R. A., & Yudkin, J. S. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(17)30221-8 · Cited by 206
Metadata
- Authors
- Demler, O. V., Paynter, N. P., & Cook, N. R.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2015-02-11
- Volume
- 34
- Issue
- 10
- Pages
- 1659-1680
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2132432664
- Cited by
- 287
- References
- 30
- FWCI
- 16.64
- Type
- journal article
- Language
- en
- Open access
- green
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