BookmarkSubscribeRSS Feed
igforek
Quartz | Level 8

Hello,

 

I run a proc MIXED on my data with a fixed factor (two infection status, InfStaStr = in, un) and some nested random factors (Stain=IsolStr=1,2,3,5 and Repeats per strain = IsolRepeatStr=A,B ...). The response is total fecundity, measured as number of eggs laid. I want to know if the infection status has an effect on total fecundity. I also want to know if the random factors are significant.The code is shown below: 

 

PROC Mixed DATA = WORK.SORTTempTableSorted covtest
PLOTS(ONLY)=ALL
METHOD=REML;
CLASS IsolStr IsolRepeatStr InfStaStr;
MODEL TotalFecundity= InfStaStr / HTYPE=3 E3;
RANDOM IsolStr IsolRepeatStrain(IsolStr) / TYPE=VC;

 

 

I am using SAS Enterprise Guide 7.1 (64-bit). I am attaching part of the output as a JPG file. The notes for the run do not indicate any problems (see attachment).

 

I need help with testing the assumptions of the analysis. I am confused in part becasue some sources define the assumptions in different ways (they seem different to me):

 

For example, The MIXED manual from SAS states the assumptions as follows:

 

-The data are normally distributed (Gaussian).
-The means (expected values) of the data are linear in terms of a certain set of parameters.
-The variances and covariances of the data are in terms of a different set of parameters, and they exhibit a structure matching one of those available in PROC MIXED.

 

Another document, the one entitled "Heteroscedasticity under the linear mixed model" states the assumption as follows:

- Normality of the random effects distribution;

- Independency of the response given the random effects i.e. independency of the errors;

- Normality of the error;

- Homoscedasticity of the error.

 

To make this matter more confusing to me, I have seen google searches from people asking for help to test for normality, homoscedasticity, and outliers (influential values) after running proc MIXED. My questions are:

 

What are the assumption to check after running proc MIXED?

How to test those assumptions and where to find clear examples of such tests?

 

I will be very obliged to anyone who can help.

 

Regards,

 

igforek

 


SAS_To_Question.jpg

Ready to join fellow brilliant minds for the SAS Hackathon?

Build your skills. Make connections. Enjoy creative freedom. Maybe change the world. Registration is now open through August 30th. Visit the SAS Hackathon homepage.

Register today!
What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 0 replies
  • 4462 views
  • 1 like
  • 1 in conversation