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Distributed Lag Linear and Non-Linear Models in R: The Package dlnm
Open accessAbstract
Distributed lag non-linear models (DLNMs) represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data. This methodology rests on the definition of a crossbasis, a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm, which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper offers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.
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Cited by
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Self-citationReducing and meta-analysing estimates from distributed lag non-linear models
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Metadata
- Authors
- Gasparrini, A.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2011
- Volume
- 43
- Issue
- 8
- Pages
- 1-20
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W4294826717
- Cited by
- 1,704
- References
- 0
- FWCI
- 28.98
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Gasparrini, A. (2011). Distributed Lag Linear and Non-Linear Models in R: The Package dlnm. Journal of Statistical Software. https://doi.org/10.18637/jss.v043.i08
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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