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Kernel Estimation of Relative Risk
Abstract
Estimation of a relative risk function using a ratio of two kernel density estimates is considered, concentrating on the problem of choosing the smoothing parameters. A cross-validation method is proposed, compared with a range of other methods and found to be an improvement when the actual risk is close to constant. In particular, theoretical and empirical comparisons demonstrate the advantage of choosing the smoothing parameters jointly. The methodology was motivated by a class of problems in environmental epidemiology, and an application in this area is described.
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Citations
Cited by
Spatial Point Pattern Analysis and Its Application in Geographical Epidemiology
Gatrell, A. C., Bailey, T. C., Diggle, P. J., & Rowlingson, B. S. (1996) · Transactions of the Institute of British Geographers · doi:10.2307/622936 · Cited by 781
Self-citationGeographically weighted Poisson regression for disease association mapping
Nakaya, T., Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2005) · Statistics in Medicine · doi:10.1002/sim.2129 · Cited by 565
Estimating intervention effectiveness in trials of malaria interventions with contamination
Multerer, L., Vanobberghen, F., Glass, T. R., Hiscox, A., Lindsay, S. W., Takken, W., Tiono, A., & Smith, T. (2021) · Malaria Journal · doi:10.1186/s12936-021-03924-7 · Cited by 9
Metadata
- Authors
- Kelsall, J. E., & Diggle, P. J.
- Venue
- Bernoulli
- Publisher
- JSTOR
- Published
- 1995-03
- Volume
- 1
- Issue
- 1/2
- Pages
- 3
- ISSN
- 1350-7265 (ISSN-L)
- OpenAlex
- W4234404834
- Cited by
- 196
- References
- 0
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Kernel Estimation of Relative Risk. https://app.cochat.ai/papers/10.2307/3318678
- The paper
- Kelsall, J. E., & Diggle, P. J. (1995). Kernel Estimation of Relative Risk. Bernoulli. https://doi.org/10.2307/3318678
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.
