Hi All, I am trying to do a data quality check on similar datasets like below. I would appreciate any help on implementing this logic:   There are two data sets with account no, start date, end date, year of transaction, month of transaction. Both datasets have different account no. but due to some reason accounts which used to be same no. are appearing in both tables with different account no. For example below in data "one", account_id 1 and account_id 8 from data "two" are same by looking at their similar start dt, end_dt AND continuation of months. I would like to combine these two accounts together.   I want to aggregate  such account numbers (append in continuation) in to separate dataset with all 5 variables.   Appreciate your help.   data one; format start_dt end_dt date9.; input acc_id start_dt date9. @13 end_dt date9. yr mth;@13 end_dt date9. yr mth; datalines; 1 01Aug2015 21JUN2021 2009 01 1 01Aug2015 21JUN2021 2009 02 1 01Aug2015 21Jun2021 2009 03 1 01Aug2015 21Jun2021 2009 04 1 01Aug2015 21Jun2021 2009 05 1 01Aug2015 21Jun2021 2009 06 2 19SEP2005 16JAN2019 2005 10 2 19SEP2005 16JAN2019 2005 11 2 19SEP2005 16JAN2019 2005 12 3 27JAN2007 14JAN2021 2007 02 3 27JAN2007 14JAN2021 2007 03 3 27JAN2007 14JAN2021 2007 04 4 23FEB2009 05JAN2032 2009 03 4 23FEB2009 05JAN2032 2009 04 4 23FEB2009 05JAN2032 2009 05 5 23AUG2009 29JAN2027 2009 09 5 23AUG2009 29JAN2027 2009 10 5 23AUG2009 29JAN2027 2009 11 ; run; data two; format start_dt end_dt date9.; input acc_id start_dt date9. @13 end_dt date9. yr mth;@13 end_dt date9. yr mth; datalines; 8 01Aug2015 21JUN2021 2009 07 8 01Aug2015 21JUN2021 2009 08 8 01Aug2015 21Jun2021 2009 09 8 01Aug2015 21Jun2021 2009 10 8 01Aug2015 21Jun2021 2009 11 8 01Aug2015 21Jun2021 2009 12 4 09SEP2005 16JAN2019 2005 10 4 09SEP2005 16JAN2019 2005 11 4 09SEP2005 16JAN2019 2005 12 7 07JAN2007 14JAN2021 2007 02 7 07JAN2007 14JAN2021 2007 03 7 07JAN2007 14JAN2021 2007 04 6 13FEB2009 05JAN2032 2009 03 6 13FEB2009 05JAN2032 2009 04 6 13FEB2009 05JAN2032 2009 05 9 23AUG2009 29JAN2027 2009 12 9 23AUG2009 29JAN2027 2010 01 9 23AUG2009 29JAN2027 2010 01 ; run; ... View more

Hi, Can anyone please suggest a way how can I randomly split the longitudinal data into training (60%) and validation (40%). In my case, I'd like split on a data set where each individual has more than one observation, in such a way that if an individual is in one of the training/validation sets, then all of their observations are in that same set.   Example data (BMILONG) below: I want to split on BMILONG dataset generated in the second step.   DATA BMI; CALL STREAMINIT(12345); DO ID = 1 TO 100; GENDER=(MOD(ID,2)=0); TREAT=( ID>50); BASELINE = ROUND(RAND('NORMAL',35,2),.1); IF GENDER=1 AND TREAT=0 THEN DO; GROUP = 'FEMALE - PLACEBO'; MONTH3 = ROUND(BASELINE - .25 + RAND('NORMAL',0,1),.1); MONTH6 = ROUND(MONTH3 + .25 + RAND('NORMAL',0,1),.1); MONTH9 = ROUND(MONTH6 - .25 + RAND('NORMAL',0,1),.1); MONTH12= ROUND(MONTH9 + .25 + RAND('NORMAL',0,1),.1); END; IF GENDER=0 AND TREAT=0 THEN DO; GROUP = 'MALE - PLACEBO'; MONTH3 = ROUND(BASELINE - 1 + RAND('NORMAL',0,1),.1); MONTH6 = ROUND(MONTH3 - 1 + RAND('NORMAL',0,1),.1); MONTH9 = ROUND(MONTH6 + 1 + RAND('NORMAL',0,1),.1); MONTH12= ROUND(MONTH9 + 1 + RAND('NORMAL',0,1),.1); END; IF GENDER=0 AND TREAT=1 THEN DO; GROUP = 'MALE - TREAT'; MONTH3 = ROUND(BASELINE - 1.5 + RAND('NORMAL',0,1),.1); MONTH6 = ROUND(MONTH3 - 1.5 + RAND('NORMAL',0,1),.1); MONTH9 = ROUND(MONTH6 - 1.5 + RAND('NORMAL',0,1),.1); MONTH12= ROUND(MONTH9 - 1.5 + RAND('NORMAL',0,1),.1); END; IF GENDER=1 AND TREAT=1 THEN DO; GROUP = 'FEMALE - TREAT'; MONTH3 = ROUND(BASELINE - 1 + RAND('NORMAL',0,1),.1); MONTH6 = ROUND(MONTH3 - 1 + RAND('NORMAL',0,1),.1); MONTH9 = ROUND(MONTH6 - 1 + RAND('NORMAL',0,1),.1); MONTH12= ROUND(MONTH9 - 1 + RAND('NORMAL',0,1),.1); END; OUTPUT; END; RUN;     DATA BMILONG; SET BMI; TIMEPT=0; BMI=BASELINE; OUTPUT; TIMEPT=3; BMI=MONTH3; OUTPUT; TIMEPT=6; BMI=MONTH6; OUTPUT; TIMEPT=9; BMI=MONTH9; OUTPUT; TIMEPT=12; BMI=MONTH12; OUTPUT; DROP BASELINE MONTH:; RUN; ... View more