R script files for modelling desert dust exposure in epidemiological short-term health effects studies.
Includes the files used in: Tobías A, Stafoggia M. Modelling desert dust exposure in epidemiologic short-term health effects studies. Epidemiology 2020;31:788-795
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The file dust_epidemiol_2020.R includes the R code to replicate step-by-step the examples in the manuscript.
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Unfortunately, due to confidentiality issues with mortality data, we are not able to distribute the example dataset. However, we are working in a simulated dataset which will be uploaded shortly.
Includes the files used for the pre-conference workshop Modelling dessert dust exposure events for epidemiological short-term health effects studies at the 31st Annual Conference of the International Society for Environmental Epidemiology, 25-28 Aug 2019, Utrecht, The Netherlands.
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The file 01.dust_models.R run all the modelling approaches simultaneously for desert dust exposures using binary and continuous metric.
- In Line 29 the dataset name must be replaced by the Users.
- In Lines 31-39 there is a description of the variable names. The Users must define the same names in their own dataset for date variable, dust exposures (dust, pm10, pm10natural, pm10local), and temperature (temp).
- In Line 52 the Users must define the health outcome in their dataset.
- In Lines 55-58 the Users must set the exposure lag of interest for their analysis.
- In Line 70 the Users can change the parameters and variables for the adjustment of the baseline time-series regression model adjusted for time-trend and temperature.
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The file 00.dust_prepdata.R is an ancillary file used by 01.dust_models.R to generate the lagged variables for dust exposures and PM10 and the smooth terms to adjust for temperature.
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Unfortunately, due to confidentiality issues with mortality data, we are not able to distribute the example dataset. However, we are working in a simulated dataset which will be uploaded shortly.