Hi, I wonder what kind of joining this kind of table it is. Could you please let me know proc sql code? data a; input year id v1; cards; 1 1 23 2 1 25 3 1 26 1 3 27 2 3 28 ; data b; input year id v2 v3; cards; 1 1 1 34 2 1 0 35 3 1 1 245 1 2 0 234 2 2 1 325 3 2 0 3 1 3 1 25 2 3 0 23 3 3 1 34 ; The expected table looks like this. year id numb v1 v2 1 1 23 1 34 2 1 25 0 35 3 1 26 1 245 1 3 27 1 25 2 3 28 0 23 3 3 . 1 34 +addition: I want to extract all the information (v2 and v3 for all years 1-3) from table b (even though there is one or two rows in table a) for only ids existing in table a.  ... View more

data have input year id v1 v2 v3; cards; 1 1 . 1 20 1 1 . 1 30 1 1 . 1 10 2 1 . 1 10 3 1 . 1 10 3 1 . 1 20 1 2 . 1 20 1 2 . 2 30 2 2 . 1 20 2 2 . 1 20 ; From this data, I want to summarize the number by id and year. What I want is...  data want; input year id v1_sum v2_sum v3_sum; cards; 1 1 . 3 60 2 1 . 1 10 3 1 . 2 30 1 2 . 3 50 2 2 . 2 40 3 2 . . . ; The code I tried is something like this:   proc sql; create table sum_diag as select person_id, year, from diagnos group by year order by person_id, year; quit;   I couldn't get the result by year. There were multiple observations  per year for several rows. What should I do to get sum by year within a subject?  ... View more

This is a typical problem that can be encountered in panel data when I want to exclude certain subjects who don't meet my inclusion criteria. For example, from the table below   year id v1 v2 v3 1 1 1 23 0 2 1 2 23 0 3 1 3 23 1 1 2 1 14 0 2 2 3 23 0 3 2 2 23 0 1 3 2 25 0 2 3 2 2 0 3 3 1 3 0  One of my criteria is that a subject that v3=1 shouldn't be included. Thus, I want to eliminate all observations from id 1 (year1-3). Likewise, I have another condition that a subject who shows decrease in v2 should not be included. Then, all observations from id 3 should be also eliminated. As a result, the table I want to see is. year id v1 v2 v3 1 2 1 14 0 2 2 3 23 0 3 2 2 23 0   What codes can I use for handling this problem? ... View more

I wonder how I can vertically join two tables based on the information of one table.   So, here are two tables.    data1       year id v1 v2 2002 1 3 3 2003 1 1 2 2002 2 1 2 2003 2 1 3 data2       year id v1 v2 2004 2 1 3 2005 2 1 2 2006 2 2 4 2004 3 2 4 2005 3 1 2 2006 3 4 2   I only want additional information from data 2 about id 1 and 2 who are in data1. Thus, the expected outcome is below. could you please help me? thanks so much..   year id v1 v2 2002 1 3 3 2003 1 1 2 2002 2 1 2 2003 2 1 3 2004 2 1 3 2005 2 1 2 2006 2 2 4   I tried following codes.    proc sql; create table clean as select * from data1 except select * from data2  group by year, id; quit;   but it doesn't produce what I want.. ... View more

I would like to make 3 variables, start, stop and event. year Id deathy deathm 2001 1     2002 1     2003 1     2004 1     2005 1 2005 1 2001 2     2002 2     2003 2     2004 2 2004 3 2001 3     2002 3     2003 3     2004 3     2005 3       The table I'd like to see is below. Can I have it through both datastep and procsql? thanks in advance.   year Id deathy deathm start stop event 2001 1     0 52 0 2002 1     52 104 0 2003 1     104 156 0 2004 1     156 208 0 2005 1 2005 1 208 209 1 2001 2     0 52 0 2002 2     12 104 0 2003 2     104 156 0 2004 2 2004 3 156 159 1 2001 3     0 52 0 2002 3     52 104 0 2003 3     104 156 0 2004 3     156 208 0 2005 3     208 260   0   ... View more

I made a table for Cox hazard regression. Data was repeatedly measured, but the outcome can only once occur because it is death. Var 1-3 are all categorical. Var 1 is time-invariant while var 2 and var3 are time-varying predictors. I wonder if I've made a right format for the analysis and if my codes for proc phreg is correct. proc phreg data=death; class var1(ref='1') var2(ref='0') var(ref='0'); model riskp*event(0)=var1 var2 var3; run;   data death; input year id var1 var2 var3 event riskp ddates; cards; 1999 1 1 3 0 0 12 . 2000 1 1 3 0 0 12 . 2001 1 1 3 0 0 12 . 2002 1 1 3 1 0 12 . 2003 2 2 3 0 0 12 . 1999 2 2 1 0 0 12 . 2000 2 2 1 1 0 12 . 2001 2 2 2 1 0 12 . 2002 2 2 2 1 0 12 . 2000 2 2 2 0 0 12 . 2001 3 2 1 0 0 12 . 2002 3 2 1 1 0 12 . 2003 3 2 1 1 1 7 201307; run; ... View more