With TYPE=CS:
You can calulate ICC manually from the values in "Covariance Parameter Estimates" table as
ICC = Common Covariance Estimate / (Residual Variance Estimate + Common Covariance Estimate)
Or use the RCORR option and let SAS to report the intraclass correlation coefficient in the "Estimated R Correlation Matrix"
REPEATED / SUBJECT=normalsubject TYPE=CS rcorr;
.....
... View more
Check this: Examples: Mixed Procedure
It give detials of how to do this with example
Search within this example for keyward [intraclass correlation coefficient]
... View more
Another way
data need (Drop= i);
set have;
array varx(5) A--E;
if SUM(A,B,C,D) > 1 then DO;
R = 1;
Do i =1 to dim(varx);
varx(i)=.;
End;
End;
Else R=.;
run;
... View more
data need (Drop= i numMissing);
set have;
array varx(*) A--E;
numMissing = cmiss(A,B,C,D);
if numMissing < 3 then DO;
R = 1;
Do i =1 to dim(varx);
varx(i)=.;
End;
End;
Else R=.;
run;
... View more
"Macro variables contain only character data. However, the macro facility has features that enable a variable to be evaluated as a number when it contains character data that can be interpreted as a number."
Introduction to Macro Variables
... View more
First let us make sure that you know that:
DATALINES (or CARDS) Informs SAS that the input data resides inside the code (in-stream data) and immediately follows the DATALINES (or CARDS) statement.
Senond thing is:
You may use the INFILE statement with the DATALINES (or CARDS) to process instream data and still utilize other INFILE options.
And here in your example INFILE options missover and length= are utilized in reading the in-stream data. Both you can read about here INFILE Statement
Finally, based on previous posts by you i can understand that you are preparing for the base certification. And what i hope is you do not be confused by this sample data code with the book. This code generate data used in the book and you are not asked to know every thing in that code at least for the base exam. You are not going to get any questions out of the exam scopes or reading difficult raw data not covered in the certification book.
... View more
127 proc glm data=Shattering method=REML covtest; ------ 22 76 ERROR 22-322: Syntax error, expecting one of the following: ;, (, ALPHA, DATA, MANOVA, MULTIPASS, NAMELEN, NOPRINT, ORDER, OUTSTAT, PLOTS. ERROR 76-322: Syntax error, statement will be ignored. 128 class code location; 129 model shatearly = code location; ERROR: No data set open to look up variables. NOTE: The previous statement has been deleted.
As stated in the log, covtest is not valid option statment for PROC GLM. PROC GLM Statement
Also method is not valid too.
... View more
data want ;set have;
retain Parturition_Order;
by DAM ANIMAL_BIRTH_DATE notsorted;
If first.DAM then Parturition_Order=1;
Else if first.ANIMAL_BIRTH_DATE then Parturition_Order = Parturition_Order +1;
run;
... View more
A large gradient suggests the parameter estimate is not located at the minimum and, thus, could be changed to produce a better model fit. If any gradient is much above 0.001, one should adjust the initial parameter estimates and rerun the program.
... View more
GCONV is one of the Convergence Criteria that you can specify in your Model statement and it is the default one if not specified explicitly in the Model statements with the value of GCONV=1E–8. And this value works as threshold value in terminating the iterative gradient-descent search which is an optimization technique that is applied to minimize the vector of error values at each iteration by starting with an arbitrary initial vector of parameter estimates and repeatedly minimizing error values in small steps.
Model convergence status section in your output is related to your model’s optimization convergence and precision. And it is important to figure out some problems like complete separation or quasi-complete separation.
... View more
