
 Dear [R] Users,
 I have implemented a linear model with this syntax:

 model<-  lm  (var_dependent ~ var_indipendent + factor +  var_indipendent : factor, dataframe)
 anova (model)
 Response: var_dependent
                                              Df  Sum Sq   Mean Sq   F value     Pr(>F)
        var_indipendent               1   20.5522   20.5522  87.8701    1.167e-14 ***
        factor                              1   0.1060    0.1060     0.4530     0.50277
        var_indipendent:factor      1   1.3861    1.3861     5..9261    0.01706 *
        Residuals                         83 19.4132  0.2339
        ---
        Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


The factor variable influence significatvly the regression. Which test I have to use to understand whom factors (i.e. in my dataset factors are the different sampling sites) influence the correlation?  
Any suggestions how to perform post-hoc comparions?
 Thanks a lot!
 Francesco Nutini

 P.S. numbers have no significance, it's just an example

 		 	   		  
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