Nelly Reduan a partag� un fichier OneDrive avec vous. Pour l�afficher, cliquez sur le lien ci-dessous.
<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb> [https://r1.res.office365.com/owa/prem/images/dc-png_20.png]<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb> Screenshot 2017-11-12 18.49.43.png<https://1drv.ms/u/s!Apkg2VlgfYyDgRAeVIM0nEajx0Fb> Hello How can I perform a bootstrap analysis from a conditional logistic regression? The model has been built using the `clogit` function (`survival` package)? The model has the following structure: mod <- clogit(event ~ forest + log_area +forest:log_time + cluster(ID_individual) + strata(ID_strata), method = "efron", data = data , x=T, y=T) Using bootstrapping, I would like to have a measure of uncertainty around the estimates of beta coefficients. I am using the following code but I don't know how to consider strata and cluster arguments. library(boot) boot.clogit <- function(data, indices){ new_data <- data[indices,] mod <- clogit(event ~ forest + log_area + forest:log_time + cluster(ID_individual) + strata(ID_strata), method = "efron", data = new_data, x=T, y=T) coefficients(mod) } boot_data <- boot(data=data, statistic=boot.clogit, R=5000) I have attached an overview of my data set. Thank you very much for your time. Best regards, Nell [[alternative HTML version deleted]]
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