Hello Seanna, here is what I can propose:
First, run the following MACRO description :
%macro genEstStmt( lm_, mlsmf);
%global &lm_.;
data &lm_; set &lm_; order=_n_; param=scan(parameter,1); level=scan(parameter,2); run;
proc transpose data=&lm_ out=_&lm_.; var row:; by effect order param level notsorted; run;
proc sql;
update _&lm_. as L
set col1=coalesce((select factor from &mlsmf. as M where L.param=M.param and L.level=M.level), col1);
proc sort data=_&lm_.; by effect _NAME_ order; run;
data _null_;
length effectList $400;
retain effectList;
set _&lm_. end=lastObs;
by _LABEL_ param notsorted;
if first._LABEL_ then
effectList = cats(effectList, "ESTIMATE '", effect, " = ", _LABEL_,"'");
if first.param then effectList=catx(" ", effectList, param);
effectList = catx(" ", effectList, col1);
if last._LABEL_ then effectList=cats(effectList,";");
if lastObs then call symput("&lm_.", trim(effectList));
run;
proc sql; drop table _&lm_.; quit;
%mend;
Then, create a small dataset describing the factors that you want to change, such as :
data myLsMeansFactors;
input param $ level $ factor;
datalines;
weekend 0 0.2857
weekend 1 0.7143
;
WARNING: Verify that the levels match the factors properly - they may be inverted...
You only need to do these steps once per SAS session.
then insert the following statement inside the proc GLM:
ods output LsMeanCoef=myIncomeAnalysis;
and before the PROC SURVEYREG procedure, the MACRO call :
%genEstStmt(myIncomeAnalysis, myLsMeansFactors);
executing thet macro will create a macro variable with the same name as your LsMeanCoef dataset containing the required ESTIMATE statements.
All you need to do then is refer to the macro variable in place of your ESTIMATE statements.
Here is how the whole thing looked in my tests:
%macro genEstStmt( lm_, mlsmf);
%global &lm_.;
data &lm_; set &lm_; order=_n_; param=scan(parameter,1); level=scan(parameter,2); run;
proc transpose data=&lm_ out=_&lm_.; var row:; by effect order param level notsorted; run;
proc sql;
update _&lm_. as L
set col1=coalesce((select factor from &mlsmf. as M where L.param=M.param and L.level=M.level), col1);
proc sort data=_&lm_.; by effect _NAME_ order; run;
data _null_;
length effectList $400;
retain effectList;
set _&lm_. end=lastObs;
by _LABEL_ param notsorted;
if first._LABEL_ then
effectList = cats(effectList, "ESTIMATE '", effect, " = ", _LABEL_,"'");
if first.param then effectList=catx(" ", effectList, param);
effectList = catx(" ", effectList, col1);
if last._LABEL_ then effectList=cats(effectList,";");
if lastObs then call symput("&lm_.", trim(effectList));
run;
proc sql; drop table _&lm_.; quit;
%mend;
data myLsMeansFactors;
input param $ level $ factor;
datalines;
weekend 0 0.2857
weekend 1 0.7143
;
proc glm data=test;
ods select LsMeanCoef;
where cals ne . & income ne . & weekend ne . & inschool ne .;
class income weekend gender;
model cals= weekend gender age income;
*weight 6yr;
lsmeans income /e;
ods output LsMeanCoef=myIncomeAnalysis;
run;
quit;
%genEstStmt(myIncomeAnalysis,myLsMeansFactors);
proc surveyreg data=test;
where cals ne . & weekend ne . & income ne . & inschool ne .;
*stratum stra;
*cluster psu;
class income weekend gender;
model cals= weekend gender age income;
*weight 6yr;
&myIncomeAnalysis;
run;
Give it a try. Tell me if it works for you.
PG
PG
