R code and data for: "Reducing and meta-analysing estimates from distributed lag non-linear models"

Gasparrini, AORCID logo and Armstrong, BORCID logo (2017). R code and data for: "Reducing and meta-analysing estimates from distributed lag non-linear models". [Data Collection]. Github. https://github.com/gasparrini/2013_gasparrini_BMCmrm_Rcodedata
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An illustration on methods for reducing estimates of bi-dimensional exposure-lag-response associations obtained by DLNMs from multiple studies, and then pooling them. The example reproduces the example included in the paper: Gasparrini A, Armstrong B. Reducing and meta-analysing estimates from distributed lag non-linear models. BMC Medical Research Methodology. 2013;13(1):1. The code set contains the following: [1] regEngWales.csv stores the daily time series data from 10 locations corresponding to regions of England and Wales in the period 1993–2006; [2] the numbered files from 01.prep.R to 06.metareg.R reproduce the results of the illustrative example. The code uses functions in the R packages dlnm and mvmeta.

Keywords

Distributed lag models, Multivariate meta-analysis, Two-stage analysis, Time series

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