Hi all,   I'm looking at values from the right and left side of the body and using PROC CORR to test for a correlation between the two sides. I have a zero-inflated data set (the zeroes are meaningful to me and thus cannot be removed), and while doing PROC CORR, I'm getting matrices back without estimates because the standard error is zero. Is there a way around this/how should this be reported?   I'm also getting scatter plots back with curved fit lines. Can I fix this somehow? Or is this just how it is because of my data? Examples of both are below, along with the code that is being used.   Thanks in advance.    PROC CORR Data=coimbra_big PLOTS=SCATTER(NVAR=all); VAR EXTLZ2CA EXTRZ2CA; run;     The SAS System The CORR Procedure 2 Variables: EXTLZ1ER EXTRZ1ER   Simple StatisticsVariable N Mean Std Dev Sum Minimum Maximum 181 0 0 0 0 0 205 0.01463 0.15587 3.00000 0 2.00000   Pearson Correlation CoefficientsProb > |r| under H0: Rho=0Number of Observations  EXTLZ1ER EXTRZ1EREXTLZ1EREXTRZ1ER . . 181 . . 129 . . 129 1.00000   205   ... View more

Hello,   I was wondering if there was a quick workaround to a problem I'm having with my data in SAS 9.4. Because of the way my data is structured, I'm not sure how to get the results I want. I'm using SAS to analyze the effects that things like age, sex, and region have on some metrics I collected from muscle attachment sites (such as porosity, bone growth, etc). I have been working with another graduate student in a statistics consulting service on my campus, but I'm not able to go back and visit him, so I'm having some trouble. Here is the code:   proc glm data=data_full plots = diagnostics; class Site Age Pre_Post Sex Region Enthesis; model metric = Age Pre_Post Sex Region Enthesis/ ss3 solution; lsmeans age/pdiff adjust = tukey; run;   Here is a sample of my data and the organization of the columns:   1 - ID number (all of the 96's are the same individual, all of the 172's are the same individual) 2 - different muscle attachment 3-18 - various metrics, such as bone growth, bone porosity, etc.  19 - site 20 - age 21 - time period 22 - sex 23 - region    96 SUBSCAPULARIS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC YA PREOTTO F CONTINENTAL 96 SUPRASPINATUS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC YA PREOTTO F CONTINENTAL 96 INFRASPINATUS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC YA PREOTTO F CONTINENTAL 96 TERESMINOR 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC YA PREOTTO F CONTINENTAL 172 SUBSCAPULARIS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC MA PREOTTO M CONTINENTAL 172 SUPRASPINATUS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC MA PREOTTO M CONTINENTAL 172 INFRASPINATUS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC MA PREOTTO M CONTINENTAL 172 TERESMINOR 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 STENJEVEC MA PREOTTO M CONTINENTAL   What I'm getting with my code: - for bone porosity, the triceps is different than the supraspinatus, and the triceps has a higher score.   What I want: - summary statistics for each muscle attachment (what the mean value is for each of the metrics at each enthesis) - a comparison of sex vs muscle attachment score (I'm kind of getting this now, but I'm getting "for bone porosity, males are higher than females" when what I want is, "for bone porosity, males are higher than females at this muscle attachment")   I hope this all makes sense. Thanks in advance!   ... View more