I have some one group pre-post data and I am looking at differences between a group variable (binary) and the pre post change in the score outcome. My code for the analysis is below:   proc glm data=data;     class group;     model pre post = group / nouni;     repeated time 2 (1 2) / printe;     lsmeans group / stderr; run; ... View more

I have a single group pre-post data, with a continuous outcome (a score), and I am looking to see if there are differences in the scores by a binary variable.   So I have a pre score, a post score, a calculated change score, and a binary (yes/no) variable for each patient (N=44).   I fit an anova and an ancova adjusting for pre scores to the data for outcome 1=post and outcome 2=change.   The residuals for both are non-normal.   Is there some sort of non-parametric version of the ANCOVA I can use? I do not want to transform as it would create difficulties in interpretations.   Code: proc glm data=x;    model post= pre|binary / solution; run;   proc glm data=x;    model change= pre|binary / solution; run;   ... View more

I have some pre-post intervention data with a continuous outcome measurement and a very small sample size. The measurements at pre and post were taken across varying levels of a certain trigger. So at pre intervention, each patient was exposed to greater and greater levels of an energy drink and heart beat was measured in response. Same was done post intervention. Each patient drank variable amounts of the energy drink, so they are not on the same scale. What statistical test would I use to assess whether if the treatment was effective in lowering the heart beat in response to increasing concentrations of the energy drink? ... View more

i have some data with multiple series i would like to panel by. I am using PROC SGPANEL, panelling by car type. I have 3 plots per car type, each in a separate series statement. I would like to label each of those curves, but I am only given the option of a string, but the labels are different per car type. How can I do this? ... View more

I have some one-group pre-post data where the outcome is a score and an IV of interest is the whether or not the subject has performed the task in the past. I am looking at this in a few ways and am wondering which one is correct:   1) GLM where outcome is the change and the IV is the past exposure. 2) GLM where outcome is the change and the IV is the past exposure, adjusting for pre scores. 3) GLM where outcome is the post and the IV is the past exposure, adjusting for pre scores. 4) repeated measures ANOVA where pre post is time 1,2 and IV is past exposure.   I also looked at the interaction for model 2 for pre score x past exposure and it was close to significant and the IV became significant (it was originally non-significant without the interaction term in the model).   Can anyone suggest which model is more appropriate and how to interpret the results, especially the significance popping up after the interaction is introduced to the model? ... View more