The DOI matches its Crossref record.
Likelihood analysis of multi‐state models for disease incidence and mortality
Abstract
Data related to life histories of individuals can be obtained in many different ways, and the usefulness of multi‐state models for statistical analysis is generally highly dependent on the type and nature of the data. In this paper, we focus on this, and present an approach to estimation for certain ‘difficult’ situations associated with retrospective or incomplete prospective observation. The paper begins with the identification of some problem areas in the analysis of data on life history processes. We discuss maximum likelihood estimation in some simple contexts and introduce a pseudo‐likelihood which enables the simple analysis of some sampling procedures. This approach is illustrated on standard retrospective and case‐cohort designs.
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Citations
Cited by
Age-Specific Incidence and Prevalence: A Statistical Perspective
Keiding, N. (1991) · Journal of the Royal Statistical Society. Series A (Statistics in Society) · doi:10.2307/2983150 · Cited by 401
Dalgård, C., Christiansen, L., Vogel, U., Dethlefsen, C., Tjønneland, A., & Overvad, K. (2013) · PLoS ONE · doi:10.1371/journal.pone.0070421 · Cited by 15
Metadata
- Authors
- Kalbfleisch, J. D., & Lawless, J. F.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 1988-01
- Volume
- 7
- Issue
- 1-2
- Pages
- 149-160
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2138681335
- Cited by
- 195
- References
- 0
- FWCI
- 3.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Likelihood analysis of multi‐state models for disease incidence and mortality. https://app.cochat.ai/papers/10.1002/sim.4780070116
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- Kalbfleisch, J. D., & Lawless, J. F. (1988). Likelihood analysis of multi‐state models for disease incidence and mortality. Statistics in Medicine. https://doi.org/10.1002/sim.4780070116
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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).
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