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]]

