Hi Dr Zalesky, 


Thank you for your excellent program. 


I am trying to compare three patient groups, where group 1 is a control, group 2 partial disease expression, and group 3 complete penetrance.
I would like to compare the three groups, assessing for whether group 1 < 2 < 3 and 1 > 2 > 3  and 1 < 3,  1 > 3

I was hoping to assess this using t-tests with FDR to perform pairwise comparisons between groups. 

I initially performed this using the following design matrix and contrast (for all three groups):
 

Patient 1 Group 1: 1 0 0
Patient 2 Group 1: 1 0 0
Patient 3 Group 1: 1 0 0
Patient 4 Group 2: 0 1 0
Patient 5 Group 2: 0 1 0
Patient 6 Group 2: 0 1 0
Patient 7 Group 3: 0 0 1
Patient 8 Group 3: 0 0 1
Patient 9 Group 3: 0 0 1

To compare Group 1 < 2: [-1, 1, 0]
To compare Group 1 > 3: [1, 0, -1]
etc

However when I instead separate my design matrix and groups to run these separately, i.e. 

Patient 1 Group 1: 1 0
Patient 2 Group 1: 1 0
Patient 3 Group 1: 1 0
Patient 4 Group 2: 0 1
Patient 5 Group 2: 0 1
Patient 6 Group 2: 0 1

To compare Group 1 < 2: [-1, 1]

Patient 1 Group 1:  1 0
Patient 2 Group 1: 1 0
Patient 3 Group 1: 1 0
Patient 7 Group 3: 0 1
Patient 8 Group 3: 0 1
Patient 9 Group 3: 0 1

To compare Group 1 > 3: [1,-1] 


I get different results. 


I presume the second way is the correct way to do this, and I am guessing that the [0] in the contrast is not ignored as I thought? What is it calculating?


Is there a better way to do this, ideally allowing covariates to be used. I don't think the ANOVA/ANCOVA will work for me as I would need a posthoc test to examine where the effect lies, which appears problematic to perform from the NBS output?


Many thanks, 

Josh