Hello everyone Not strictly an R question but close... hopefully someone will be able to help. I wish to compare the switchpoints in two switchpoint regressions. The switchpoints were estimated using the segmented library running in R, and I have standard errors for the estimates. I initially thought I could just bootstrap confidence intervals for the difference between the switchpoints, but I have been having trouble with getting this to work because for about 25% of the bootstrap samples the algorithm in segmented fails to converge. So I had another think, and I thought that maybe I could just do a t-test: knowing the estimated switchpoints and their standard errors I can easily calculate the SE of the difference, so I can calculate a t-value using that. My question is whether there is anything wrong with doing it this way, and if not, how many degrees of freedom should I use? I would guess at df=n1-5+n2-5 5 df lost for each sample because two slopes, two intercepts and one switchpoint have been estimated, but I'm not sure: I'm but a humble biologist and not very good at this sort of thing.
Any help gratefully received Thanks Rob Knell School of Biological and Chemical Sciences Queen Mary, University of London 'Phone +44 (0)20 7882 7720 Skype Rob Knell Research: http://webspace.qmul.ac.uk/rknell/ "The truth is that they have no clue why the beetles had horns, it's the researchers who have sex on the brain and everything has to have a sexual explanation. And this is reasearch?!" Correspondent known as FairOpinion on Neo-Con American website discussing my research. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
