The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Survival probabilities (the Kaplan-Meier method)
Open accessAbstract
As we have observed,1 analysis of survival data requires special techniques because some observations are censored as the event of interest has not occurred for all patients. For example, when patients are recruited over two years one recruited at the end of the study may be alive at one year follow up, whereas one recruited at the start may have died after two years. The patient who died has a longer observed survival than the one who still survives and whose ultimate survival time is unknown. The table shows data from a study of conception in subfertile women.2 The event is conception, and women “survived” until they conceived. One woman conceived after 16 months (menstrual cycles), whereas several were followed for shorter time periods during which they did not conceive; their time to conceive was thus censored. View this table: Time (months) to conception or censoring in 38 sub-fertile women after laparoscopy and hydrotubation2 We wish to estimate the proportion surviving (not having conceived) by any given time, …
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Citations
Cites
Time to event (survival) data: Table 1.
Altman, D. G., & Bland, J. M. (1998) · BMJ · doi:10.1136/bmj.317.7156.468 · Cited by 175
Self-citation
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Metadata
- Authors
- Bland, J. M., & Altman, D. G.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 1998-12-05
- Volume
- 317
- Issue
- 7172
- Pages
- 1572-1580
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- OpenAlex
- W1503899947
- Cited by
- 824
- References
- 1
- FWCI
- 4.82
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bland, J. M., & Altman, D. G. (1998). Survival probabilities (the Kaplan-Meier method). BMJ. https://doi.org/10.1136/bmj.317.7172.1572
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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.
