Yes, taking repeated measures on the exact same plants.  ... View more

I have attached the raw N% data.      ... View more

Thank you so much!! ... View more

Thanks for your reply. So to be more specific, N data was collected for each foliar spray treated plant on May, July, August, September. Some other plants measured only on August and September. ... View more

N test was actually measured 4 times during the experiment but I averaged all 4 time points and put as one data for each foliar spray treatment. But this may change the code, and it looks like I could have done with the repeated measures. Maybe the zero estimates and no variability stem from there.    glimmix  code does not work for biomass and THC, even though these parameters are measured once only.  ... View more

I remember that I got these warnings in the log. What do data issues mean? Is the type of the data or collected data erroneous?  ... View more

Thanks for all your help. @Ksharp @Rick_SAS  The reason why I want to use Lsmeans statement is that I want to see differences in groups (fertilizers) and weeks, if any. When I run the code, I do not see p values in fixed effects.  ... View more

Hello Rick,    Thanks for your reply. I've attached the data. I tried both glimmix and proc gee, but I still got stuck. @Rick_SAS    frt=fertilizer  I collected data for 27 weeks for the same plants sprayed with different fertilizers, and I am looking to see if there is any significant difference between fertilizer treatments on plant height and biomass.      Proc gee Data =Waterford; class frt week; model ph=frt; repeated subject=frt/type=ar(1) covb ; lsmeans frt*week/ cl diff plot=diff Adjust=Tukey lines; run;   Error: Effects used in the LSMEANS statement must have appeared previously in the MODEL statement.     Proc glimmix Data =Waterford; class frt week; model ph = frt week frt*week/link=log dist=multinomial; random week/subject=frt type=cs residual; lsmeans frt*week / Adjust = Tukey lines slicediff= week; output out=second predicted=pred residual=resid residual(noblup)=mresid student=studentresid student(noblup)=smresid; run;   For the multinomial distribution only the following links are possible: CUMLOGIT, CUMPROBIT, CUMLOGLOG, CUMCLL, GLOGIT.   Thank you again.  ... View more

Where am I making a mistake? Should I use proc gee instead of proc glimmix? or I can not use probably lsmeans multinomial distributions?    proc glimmix data=waterford; class frt height biomass;  model frt= biomass height; lsmeans biomass height/ Adjust = Tukey lines slicediff= frt; run;    ERROR: Least-squares means are not available for the multinomial distribution. ... View more

I could have said, there are replications but not equal. But again, it does not apply to all treaments. I think it is counted that there are replications.   I did run it and gave an error.  'ERROR: ''Effects used in the LSMEANS statement must have appeared previously in the MODEL statement'' ... View more

I have replications of some treatments but not all of them; I want to analyze them as an individual treatment. But in general, I wouldn't say the experiments have replications as they do not apply to all. Might be the reason why it says there are multiple observations. In this case, is this the correct code? proc glimmix data=LP; class frt height biomass; model frt= biomass; lsmeans frt*biomass / Adjust = Tukey lines slicediff= frt; run; ... View more

I've corrected that one in SAS. It is a letter from a treatment name with a space in between. I would like to have a pairwise comparison of treatments ( fertilizers) with letters. The hypothesis is that the fertilizers will increase the plant height.    I tried adding;    Proc gee Data =Waterford; class frt week; model ph=frt; repeated subject=frt/type=ar(1) covb corrb; lsmeans frt/ pdiff=all adjust=tukey LINES; run;   Error: Only CLASS variables allowed in this effect. Is it because we added cov, which is already LS means of covariances?      Thanks Steve!        ... View more

Yes, I use SAS studio. Thank you very much again. ... View more