Hi! > When you do this, you are including all the > interaction terms. > The * indicates an interaction, as opposed to +.
In this particular case I need to do exactly this; this is a study of antibiotic resistance - two of the variables respectively are type of bacteria and antibacterial agent. The evolutionary/epidemiological behavior of each pairing of these factors is different. Can I remove some lower order terms; for example, if I get rid of Bugtype:Usage.level.ofdrug and Drugtype:Usage.level.of.drug will Bugtype:Drugtype:Usage.level.of.drug still be valid? > If you select predictors on the basis of which ones > are > significant, then the final significance levels > don't mean much, > usually. Remember, 1 out of 20 will be significant > at .05 even > if you are using random numbers. > This is an excellent point; were I to proceed I would need to select based strictly on removing from collinear pairs or groups of explanatory variables, probably according to an a priori established ordering of classes of variables; ie B:D:U might be more interesting than B:U or D:U or B:D:U:ICU, so remove collinear variables from the latter three first, irrespective of statistical significance. Thanks for you help. :-) -petertgaffney ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
