Hello,   I normally use (param=ref ref=...) in my coding so I easily find the parameters in my model but I am having difficulty finding the right parameters for log-linear saturated model when it is coded as (param=reffect)   In the attached pictures, I am looking for the parameters that are associated with blond hair and hazel eye color.(hazel is reference category) My program is below;   proc genmod data=students; class hair (param=effect) eye (param=effect); model ct = hair eye hair*eye/ dist=poisson link=log obstats; run;   I am getting below which is not giving me the correct number. ln(μ24)=3.1895(intercept)+(-0.2985) (blonde hair)=   Please help me understand what I am missing here.   ... View more

I have been trying to get predicted probability for each count. I am putting code "predicted=" after model statement but that is giving me the mean of poisson. How can I get predicted probability based on poisson for each count and graph it?   data world; input scores @@; datalines; 4 3 3 3 2 4 2 0 3 3 3 2 4 2 1 1 1 3 7 3 2 2 2 5 .......... ; proc genmod data=world; model scores= /dist=poisson link=log; output out=new predicted=predictedscores; run; quit; ... View more

Hello, I am a beginner stat student. I am trying to plot observed and predicted Poisson and negative binomial probabilities against the data observed. I have no experience or prior knowledge of graphing. I am getting lost in all complex explanations. Can you please help me in simplest way of accomplishing this task?   Below is my syntax. How do I plot predicted Poisson and negative binomial probabilities against the sample below? data world; input scores @@; datalines; 5 1 6 3 2 1 2 1 1 2 1 3 3 3 3 4 1 1 1 2 1 3 2 2 3 7 3 3 7 4 3 3 3 2 4 2 0 3 3 3 2 4 2 1 1 1 3 7 3 2 2 2 5 ; proc means data=world n mean var; run; /* Mean= 2.67 and Variance=2.56. The data is a good canfidate for poisson distribution. */ proc genmod data=world; model scores= /dist=poisson link=log; run; ... View more