SAS Support Communities

DATA HAVE; INPUT ID YEAR WEIGHT HEIGHT SMOKING EXERCISE DATELINES; 01 2000 . 175 . 1 01 2001 57 175 1 1 01 2002 . 175 . 1 01 2003 57 175 1 1 01 2004 . 175 . 1 02 2000 57 . 1 1 02 2001 . 168 . 1 02 2004 57 169 1 1 DATA HAVE; INPUT ID YEAR WEIGHT HEIGHT SMOKING EXERCISE DATELINES; 01 2000 57 175 1 1 02 2000 57 168 1 1 ... View more

    The are both continuous an categorical variables. The data is arranged with person      Data structure before   ID    YEAR    WEIGHT    HEIGHT     SMOKING    EXERCISE   01    2000           .              175                   .                  1 01    2001           57           175                  1                  1 01    2002           .              175                   .                  1 01    2003           57           175                  1                  1 01    2004           .              175                   .                  1 02    2000           57             .                     1                  1 02    2001           .              168                  .                  1 02    2004          57            169                  1                  1     Data structure after(Only one observation per person with missing values for year 2000 values imputed .     ID    YEAR    WEIGHT2000   HEIGHT2000   SMOKING2000    EXERCISE2000 01    2000            57               175                           1                          1 02    2000            57                168                          1                          1       I want to have the values for the first year imputed so that I use the information for the first year in my analysis. There many observations per person and the number of observations is not similar but I want to have one summary of imputed data for each person(One entry per person).   Thank you for assistance.                ... View more

  This is the  log file from the code I tried. The variable Time is the follow up time but its excluded from the output data created and selection procedure is ignored.   Below is the log file.     NOTE: The SELECTION= option (MODEL statement) is ignored for the Fine and Gray competing-risks analysis. NOTE: SLSTAY= is ignored since SELECTION=NONE. NOTE: DETAILS is ignored since SELECTION=NONE. NOTE: Data for variable Time in the COVARIATES= data set are not copied to the OUT= data set in the BASELINE statement.     ... View more

The data sets are directed to the external hard drive and I have them read but plotting them is the problem. But I have not understood exactly how to increase my memsize. Which procedure do i use?   Thanks. ... View more

I am using SAS 9.4 University Edition and I will take any advise you give me so that I can solve the problem.   I also think visualizing reduced number of observation would be best and I was trying to reduce the data using proc KDE and save the output data but this error didn't allow.     Thank for responding. ... View more

  How to increase memory usage in SAS will be of good help for the start and I see if its memory problem.      I think all the 3 above can solve the problem am encountering. I dont know exactly what the problem is because the data is extremity big more than 8,000,000,000 observations.    If possible help me with method to increase memory and plotting all points.     Thank you for the quick response and assistance. ... View more

Am using Proc phreg like the code below.   Proc phreg data=Variation; class Gender(ref='Male') INCOME(ref='HIGH'): model Time * Status (0)= Gender INCOME / rl; Selection=None details; Output Out=Variations Survival=Survest; run;     How can I obtain R2 if am using proc phreg?     I will be glad for your assistance. ... View more