Code for Schnell, Bandyopadhyay, Reich & Nunn, "A marginal cure-rate proportional hazards model for spatial survival data." Journal of the Royal Statistical Society, Series C (2015)
schnellp/JRSSC-2015-SpatialSurvival
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A marginal cure-rate proportional hazards model for spatial survival data Description of Data Set mcguire.csv is a text file containing comma-separated data. The first row consists of column headers. Of interest in the paper are the following: - id: subject ID - tooth: tooth number - smoke: smoking status (1 = smoker) - age: age (years) at baseline - hygiene1: hygiene rating ([G]ood, [F]air, [P]oor) - cr0: crown-to-root ratio at baseline - probe0: baseline probing depth - mobile0: baseline mobility - time: time of last observation (event or censoring time) - censor: right-censoring indicator (1 = censored) Programs and Use - load_data.R loads the raw data from mcguire.csv, produces objects useful for the method presented in the paper, and saves the result as NunnData.RData, which is used directly in subsequent scripts. - MCMCfx_PS_factor_PCURE.R fits the positive stable model via MCMC. - MCMCfx_Gauss_PCURE_NUfixed.R fits the competing Gaussian random effects model via MCMC. This is a modification of MCMCfx_PS_factor_PCURE.R. - MCMCfx_Ind_factor_PCURE.R fits the competing independence model via MCMC. This is a modification of MCMCfx_PS_factor_PCURE.R. - FitPSmodel.R loads the example data set and calls MCMCfx_PS_factor_PCURE.R to fit the positive stable model. - summarize.R produces summary statistics and various plots from a model fit. - callSim.R simulates data sets and fits three competing models via the MCMCfx[...] scripts. Results are output to the "results/" folder. The first set of three fits is saved to results/fit.RObject, and a table of results is updated after each set of three fits is completed and saved as results/partialResult.#.RObject. For questions, please contact Brian Reich at brian_reich@ncsu.edu.
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Code for Schnell, Bandyopadhyay, Reich & Nunn, "A marginal cure-rate proportional hazards model for spatial survival data." Journal of the Royal Statistical Society, Series C (2015)