

   Dear list: 


   After several analyses, I get a significant effect in a factor with 7 levels. As I am doing a stepwise simplification, I get my p-values from the anovas comparing pairs of models. But that way, I obviously get only one p-value for the factor, but I can't know which of the levels are the most important ones in determining that effect. I have an idea from the p-values of the "summary" table, and I can also plot the data to see the direction of the effect. However, I have read in a paper that there is a method to collapse factor levels to obtain information about which factor levels differ from one another, that is used when an
explanatory variable has a significant effect in the minimal model and contains more than two factor levels. I have looked for it in teh Crawley book and in the web, but I actually cannot find anything, and I don't know which terms are more appropriate for searching. 

   Does any of you know about this method, and if so, can he/she tell me where I can find an appropriate description? I would very much appreciate any information.

   Thank you very much. 


 ________________________________________

   Iker Vaquero-Alba
   Centre for Ecology and Conservation
   Daphne du Maurier Building
   University of Exeter, Cornwall Campus
   Treliever Road
   TR10 9EZ Penryn
   U.K.

   http://biosciences.exeter.ac.uk/cec/staff/postgradresearch/ikervaquero-alba/

	[[alternative HTML version deleted]]


