Hello SAS Community, I am working on an observational study to determine the impact of a program. My approach is to compare the results of the treatment group to a control group. I thought this would be a good approach because I could control for possible confounding variables by using a one to one match on these variables.   After presenting some initial results most of the feedback has been additional variables that should have been controlled for. Is there a way to control for additional variables using the existing control/treatment populations and save my analysis? Or do I just keep collecting more data and constructing new control populations?   For example, if I constructed a control group to compare to the treatment group but failed to control for height of an individual and my populations are not balanced on this variable, is there a way to analyze the data control for height? Such that I can reliably extract the impact of the program?   I have been learning as I go on this project and I suspect this might be a simple/silly question for more experienced statisticians. I am asking in general to figure out what techniques or procedures I need to learn more about. ... View more

Hello,   If this is my starting data: data have; infile datalines dsd dlm=','; input person $ status date yymmdd10.; format date yymmdd10.; datalines; a,.,2019-02-01 a,0,2019-03-01 a,1,2019-04-01 a,0,2019-05-01 a,1,2019-06-14 a,0,2019-12-31 b,.,2019-01-31 b,0,2019-03-01 b,1,2019-05-03 b,1,2019-05-04 c,0,2019-01-30 c,0,2019-01-31 c,1,2019-07-06 c,1,2019-07-07 d,1,2019-03-06 e,0,2019-06-01 f,.,2019-02-01 f,0,2019-03-01 f,1,2019-04-01 f,1,2019-05-01 f,0,2019-06-14 f,1,2019-11-30 f,1,2019-12-31 ; run; How do I get the following results? data want; infile datalines dsd dlm=','; input person $ status date yymmdd10.; format date yymmdd10.; datalines; b,1,2019-05-03 c,1,2019-07-06 d,1,2019-03-06 f,1,2019-11-30 ; run; Where the members returned have a last status of 1 and the date returned is the first date where status = 1 and there is no later status of 0 or null.   Person 'a' doesn't get returned because their last status is not 1. Person 'b' gets returned with a date of 2019-05-03. Their last status = 1 and that is the earliest date of status 1 with no following statuses <> 1 Person 'c' gets returned with a date of 2019-07-06. Their last status = 1 and that is the earliest date of status 1 with no following statuses <> 1 Person 'd' gets returned with a date of 2019-06-06. Their only status = 1 Person 'e' doesn't gets returned because their only status <> = 1 Person 'f' gets returned with a date of 2019-11-30. Their last status = 1 and that is the earliest date of status 1 with no following statuses <> 1. In this example we wouldn't return the date of 2019-04-01 because there is a subsequent event with a status <> 1 on 2019-06-14.   How can I code to get the desired output? ... View more

I am producing a summary report that gets put into an email. We primarily use Outlook for our email. The summaries look pretty good but there is a large gap between the first and second titles. How do I reduce the gap between titles? For example, when I run this code: /** get email ready **/ filename email email from = "from email" to = ("to_email") subject = "Test" type ="text/html"; /** Clean up report **/ proc template; define style styles.myexcel; parent=styles.excel; class body / backgroundcolor=_undef_; class systemtitle / backgroundcolor=_undef_; class paragraph / backgroundcolor=_undef_; end; run; ods _all_ close; ods msoffice2k style = myexcel body = email; proc report data = sashelp.cars(obs=10) nowd style(header) = {color = white background = #003C71} style(report) = {just = left bordercollapse = collapse}; title1 justify=left bold h=12pt "Title 1"; title2 justify=left bold h=10pt "Title 2"; columns make model type; define make / display "Make"; define model / display "Model"; define type / display "Type"; run; ods msoffice2k close; I get this output:   ... View more