Armstrong, BG, Gasparrini, A and Tobias, A. 2017. R and STATA code for: "Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis". [Online]. Github. Available from: https://github.com/gasparrini/2014_armstrong_BMCmrm_Codedata
Armstrong, BG, Gasparrini, A and Tobias, A. R and STATA code for: "Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis" [Internet]. Github; 2017. Available from: https://github.com/gasparrini/2014_armstrong_BMCmrm_Codedata
Armstrong, BG, Gasparrini, A and Tobias, A (2017). R and STATA code for: "Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis". [Data Collection]. Github. https://github.com/gasparrini/2014_armstrong_BMCmrm_Codedata
Description
Illustration of conditional Poisson models as an alternative method in analyses of environmental data. In particular, this represents a computationally convenient alternative to both conditional logistic case-crossover models (when data are aggregated in time series form) and to standard Poisson regression for long time series (when control for time is achieved with computationally expensive spline functions). The code follows the examples included in the associated article that illustrates the methodology and some applications. The material includes: [1] londondataset2002_2006.csv stores the dataset used in the illustrative examples; [2] funccmake.R generates the R function to convert data from time series to case-crossover formats; [3] Rcode.R is the R code to reproduce the examples; and [4] Statacode.do is the Stata code to reproduce the examples.
Data capture method | Other |
---|---|
Date (Date published in a 3rd party system) | 15 January 2017 |
Language(s) of written materials | English |
Data Creators | Armstrong, BG, Gasparrini, A and Tobias, A |
---|---|
LSHTM Faculty/Department | Faculty of Public Health and Policy > Dept of Public Health, Environments and Society |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 13 Dec 2018 14:22 |
---|---|
Last Modified | 08 Jul 2021 12:52 |
Publisher | Github |