Journal
JOURNAL OF STATISTICAL SOFTWARE
Volume 43, Issue 8, Pages 1-20Publisher
JOURNAL STATISTICAL SOFTWARE
DOI: 10.18637/jss.v043.i08
Keywords
distributed lag models; time series; smoothing; delayed effects; R
Funding
- Medical Research Council [G0701030] Funding Source: researchfish
- Medical Research Council [G0701030(82641), G0701030] Funding Source: Medline
- MRC [G0701030] Funding Source: UKRI
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available