Hello all, I am busy on a study to compare different types of sowing type for field margins to attract bumble bees. I have three blocks, and within those blocks there are the four different treatements (fixed effects). There are 4 different moments in which i counted the bees, I would like to know if the sowing types have a significant effect on the counts of the bees and wether they differ pairwise from each other This presents me with a lot of problem solving to do in stating my model, i cannot find any examples which are similar. This is my data data hommel; input loc $ meng count; cards; a    g    29 b    g    43 c    g    10 a     i    24 b    i    66 c    i    23 a     k    83 b    k    73 c    k    60 a     t    45 b    t    75 c    t    48 run; I came up with the following code: proc glimmix data=hommels; class mengsel loc; model count=mengsel/dist=poisson link=log solution; random loc; random _residual_; lsmeans mengsel/cl ilink;, run; i did a dist=poisson because it are counts, log link for the same reason random component is the block of the location and then i try to correct for overdispersion because it looked the right way to do... the cl ilink for giving me the real estimates, but this does not seem to work either.. I am not sure if this is the right way to go with this, so i do not want to jump in conclusions and not i am not even sure what the conclusions would be fro this, i do not get a t value for fixed factor t? I would really like to know how i could solve this...also an output of this does not render me pairwise comparison as the output of a proc mixed can give thanks, martijn ... View more