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Distributed Lag Linear and Non-Linear Models in R: The Package dlnm.

ABSTRACT: 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.

SUBMITTER: Gasparrini A

PROVIDER: S-EPMC3191524 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Distributed Lag Linear and Non-Linear Models in R: The Package dlnm.

Gasparrini Antonio A

Journal of statistical software 20110701 8

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 ...[more]

PMID: 22003319

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