Hello, I do have a dataset partly consisting of possible "pseudo replicates". I'd like to use a bootstrap approach to assess the influence of them.
My dataset looks like this minimal example: y <- c(1,5,6,2,5,10) # response x1 <- c(2,12,8,1,16,17) # predictor 1 rep <- c(1,2,2,3,4,4) # pseudo replicates df <- data.frame(y,x1,rep) model <- lm(y~x1, data=df) The variable rep represents kind of pseudoreplicates. I'd like to randomly select for each bootstrap step only one case per number (1,2,3,4). So I want to select always one case per group of rep. I hope you understand what I mean. In the end I'd like to get the %variation in the regression parameter estimates. How can I do that using boot together with lm? I had already a look in help(boot), but it is still very confusing to me. Hopefully you can help me. Best regards, Johannes -- _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
