[R] t-values for two-way interactions

[R. Baker]

I have a model with 3 fixed factors (type, stress, MorD) and two 
significant two-way interactions (type*stress, stress*MorD).

x$summary

#                  Estimate Std.Error  DF t.value pvals ci950 ci990 ci999

#(Intercept)        241.738     8.757 994  27.606 0e+00  TRUE  TRUE  TRUE

#typePsPr           -26.516     5.905 994  -4.490 1e-05  TRUE  TRUE  TRUE

#stressPN           -21.820     1.776 994 -12.284 0e+00  TRUE  TRUE  TRUE

#MorDMis            -26.588     5.905 994  -4.503 1e-05  TRUE  TRUE  TRUE

#typePsPr:stressPN   13.904     2.051 994   6.779 0e+00  TRUE  TRUE  TRUE

#stressPN:MorDMis     9.168     2.051 994   4.470 1e-05  TRUE  TRUE  TRUE


I would like to find out more about the type*stress interaction, e.g. how 
the levels of type differ between stress. More specifically I want to find 
a t-value for the pairwise comparisons:

typePr:stressN vs. typePsPr:stressN
typePr:stressPN vs. typePsPr:stressPN

I can't do this with the summary table (above) as it always includes the 
factor MorD (mis/dis) in each pairwise comparison, i.e. it provides 
t-values for

typePr:stressN:MorDmis and typePsPr:stressN:MorDmis 
typePr:stressN:MorDdis and typePsPr:stressN:MorDdis 

Is it possible to look at interaction of type*stress over MorD and NOT 
within MorDmis or MorDdis?

Any advice would be greatly appreciated!

Rachel Baker

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PhD student                
Dept of Linguistics        
Sidgwick Avenue
University of Cambridge              
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