Hello Everyone,   Following on the post by zzecon (https://communities.sas.com/t5/SAS-Procedures/Making-a-publication-quality-table-from-regression-results-using/td-p/396779) I would also like to produce regression output like this one: Using the following code, I get a slightly diffferent output.   proc format; picture stderrf (round) low-high=' 9.9999)' (prefix='(') .=' '; run;   proc report data=parmest nowd out=table; column type dependent variable value1 value2; define numord /noprint; define variable /display ' '; define type / display; define dependent / across ' '; define value1 /display; define probt1 /display; define value2 /display; define probt2 /display; compute value; array cc _c8_ _c5_ ; if type='stderr' then do; call define(_col_,'format','stderrf.'); end; else do; call define(_col_,'format','8.4'); do i= 1 to 3; if ~missing(cc(i)) then do; if 0.05<cc(i) <= 0.1 then call define(_col_, "style", "style=[ posttext='*']" ); else if 0.01 <cc(i) <=0.05 then call define(_col_, "style", "style=[ posttext='**']" ); else if cc(i) <= 0.01 then call define(_col_, "style", "style=[ posttext='***']" ); leave; end; end; end; endcomp; run; This is what my output table looks like: type indavgcost   value1 value2 coefficient 1 Intercept 2154.033 2361.4119 stderr 1 Intercept 3.9858111 22.628486 coefficient 1 tag13 101.8107 73.756248 stderr 1 tag13 8.189885 8.1373222 coefficient 1 avgcontract -736.7952 -578.251 stderr 1 avgcontract 10.062152 10.037246 coefficient 1 tag13*avgcontract -80.84143 -100.5845 stderr 1 tag13*avgcontract 20.23273 20.126612 coefficient 1 ses . -74.14517 stderr 1 ses . 2.3641456 coefficient 1 female . -54.42843 …..                   I want the standard errors to be parenthesis. I would like to see the stars next to the coefficient.  The mistake will be in the array of my proc report, but I don’t know what exactly. Thanks for your help. ... View more

  Hello Everyone,   Following on the post by zzecon (https://communities.sas.com/t5/SAS-Procedures/Making-a-publication-quality-table-from-regression-results-using/td-p/396779) I would also like to produce regression output like this one: Using the following code, I get a slightly diffferent output.   /*write a dataset with standard error on the same column of coefficient*/ data parmest_; set work.parmest; if not missing(stderr) and variable not in ('R-Square','Root MSE','N. Obs.') then do; value=estimate; type='coefficient'; output; end; if not missing(stderr) then do; value=stderr; type='stderr' ;output; end; if variable in ('R-Square','Root MSE','N. Obs.') then do; value=estimate; type=variable ;output; end; run; proc format; picture stderrf (round) low-high=' 9.9999)' (prefix='(') .=' '; run;   　 proc report data=parmest_ nowd out=table; column numord variable type dependent, (probt value); define numord /group order=data noprint; define variable / group order=data ' '; define type / group order=data noprint; define dependent / across ' '; define value /analysis sum; define probt /analysis sum; compute value; array cc _c8_ _c6_ _c4_ ; if type='stderr' then do; call define(_col_,'format','stderrf.'); end; else do; call define(_col_,'format','8.4'); do i= 1 to 3; if ~missing(cc(i)) then do; if 0.05<cc(i) <= 0.1 then call define(_col_, "style", "style=[ posttext='*']" ); else if 0.01 <cc(i) <=0.05 then call define(_col_, "style", "style=[ posttext='**']" ); else if cc(i) <= 0.01 then call define(_col_, "style", "style=[ posttext='***']" ); leave; end; end; end; endcomp; run;   This is what my output table looks like:   I see two problems: 1. I have two regressions.  I would like to see the output side-by-side (as above) I only see one here. 2. the coefficients and standard error values are actually different than in my table (attached), as if I would changing it unintentionally.   Thanks for your help.     indavgcostPr > |t| value Intercept <.0001 8453.102***   <.0001 (1.3810) tag13 0.7400 -127.069   0.7400 (9.6254) avgcontract <.0001 -1224.34***   <.0001 (8.2317) tag13*avgcontract 1.5562 46.4737   1.5562 (2.5511) ses 0.0530 -42.3237*   0.0530 (1.8749) female 0.0064 -780.368***   0.0064 (6.3947) age_gr <.0001 -2138.21***   <.0001 (4.8519) age_gr <.0001 -1909.67***   <.0001 (4.0391) age_gr <.0001 -1802.40***   <.0001 (2.4117) age_gr <.0001 -1830.20***   <.0001 (0.5354) age_gr <.0001 -1448.62***   <.0001 (3.2364) age_gr <.0001 -1609.45***   <.0001 (1.8672) age_gr <.0001 -1557.71***   <.0001 (4.7518) age_gr <.0001 -1618.78***   <.0001 (1.6792) age_gr <.0001 -1112.25***   <.0001 (4.4247) age_gr <.0001 -1069.81***   <.0001 (3.9204) age_gr <.0001 -1245.90***   <.0001 (0.5962) age_gr <.0001 -1336.19***   <.0001 (7.3560) age_gr <.0001 -1608.00***   <.0001 (6.7212) age_gr <.0001 -1644.24***   <.0001 (7.9121) age_gr <.0001 -993.303***   <.0001 (8.1234) age_gr <.0001 -1310.02***   <.0001 (2.4610) age_gr <.0001 -1282.29***   <.0001 (9.3784) age_gr 0.5106 210.1890   0.5106 (9.4449) age_gr 0.0015 -1615.85***   0.0015 (0.1211) female*age_gr 0.0013 1127.503***   0.0013 (0.1875) female*age_gr 0.0033 992.5148***   0.0033 (7.4810) female*age_gr 0.0353 694.6752**   0.0353 (9.9497) female*age_gr 0.0659 623.0732*   0.0659 (8.8363) female*age_gr 0.1377 504.2382   0.1377 (9.6422) female*age_gr <.0001 1491.246***   <.0001 (3.3474) female*age_gr <.0001 1339.971***   <.0001 (8.7947) female*age_gr 0.0010 1102.112***   0.0010 (4.9940) female*age_gr 0.0991 536.0772*   0.0991 (5.0355) female*age_gr 0.9996 -0.1699   0.9996 (4.0705) female*age_gr 0.0296 700.1651**   0.0296 (1.9080) female*age_gr 0.0951 534.5546*   0.0951 (0.2453) female*age_gr 0.0134 788.9965**   0.0134 (9.1323) female*age_gr 0.1294 491.9362   0.1294 (4.3554) female*age_gr 0.0600 624.4005*   0.0600 (1.9166) female*age_gr 0.0006 1197.305***   0.0006 (8.4239) female*age_gr 0.0184 860.5910**   0.0184 (5.0921) female*age_gr 0.0267 -959.616**   0.0267 (2.9871) female*age_gr 0.1352 921.4893   0.1352 (6.853) ... View more

Hi,   I have the following code, which I need to run multiple times (i=1 to 100) on different datasets. I need to save the datasets separately. How can I do this most efficiently? Thanks,   **************************************** data claims_1; input client year cost contract; datalines;   18 2011 589.92 10.2 19 2010 1629.8 11.5 20 2011 1813.29 2.3 21 2012 412.06 3.2 22 2012 219.82 0.4 23 2010 3669.98 5.9 24 2012 4879.63 6.8 ; run;   /*GENERAL HOSPITALS*/ proc glm data=claims_1; class year (ref='2010' ); model cost=year|contract/ solution; ods output ParameterEstimates=work.parmest_1 fitstatistics=fit_1 nobs=nobs_1; run; data parmest_1; set parmest_1; rename Parameter=Variable; run; data parmest_1; set parmest_1; numord+1; if first.variable then numord=1; run; data nobs_1; set nobs_1; if label^="Number of Observations Used" then delete; keep Nobsused Variable numord; Variable="N. Obs."; rename NObsUsed=Estimate; numord=2000; run; data fit_1; set fit_1; keep RSquare RootMSE; run; proc transpose data=fit_1 out=fit_1; run; data fit_1; set fit_1; if _Name_="RSquare" then numord=1000; if _Name_="RootMSE" then numord=1001; rename _Label_=Variable; drop _name_; rename col1=Estimate; run; data work.parmest1; set work.parmest_1; run;   ** append parmest_1; proc datasets; append base=work.parmest1 data=work.nobs_1 force; run; append base=work.parmest1 data=work.fit_1 force; run; quit;     ... View more

Hi,    I have a simple do-loop:   data nobs;        do i=i to 2; data nobs_i;    set nobs_i; keep Nobsused; end; run;   It is giving me the following error msg: No Matching DO/SELECT statement. Why?   ... View more