You are looking for variables selection method. Check SELECT= option of MODEL statement.
I don't see a "Select=" option. There is a Selection= which specifies a specific model to use e.g. None, Forward, Backward etc but I see no option for a Sequential or Hierarchical regression which would allow me to enter the variables in a specific order. Rick_SAS suggested the SEQB option which produced parameter estimates for each variable as it was entered in the regression but I'm not convinced that it actually conducted a sequential regression. Changing the order of the variables in the variable list did not change the parameter estimates in the SEQB output which makes me think the PROC REG is selecting the variable order based on R or a t-value and not necessarily on the order I want them.
Geoff
If you want "Changing the order of the variables in the variable list DID change the parameter estimates " you could try PROC GLM .
Sorry. Maybe I misunderstood your question. But from what you described , it looks like you need to resort to MIXED model. PROC MIXED
Or you could try proc glmselect data=sashelp.cars; model enginesize= cylinders horsepower invoice length/selection=none; run;
Hi, thanks for the suggestioon but it produced the exact same parameters as the PROC REG Selection=none model. Basically a full regression model and the order that the vriables were entered into the model didn't change the parameter estimates. Am I wrong to think that if a true sequential regression was being carried out then the order the variables are entered into the model should affect the parameter estimates? If not can somone provide an example where the parameter estimates change with the order of the variables.
Thanks
Geoff
Hi Geoff,
Do you happen to have syntax for the solution you found here in your last reply? I am also looking to do this type of model (except in proc surveylogistic) so I am taking your suggestion of running separate regressions, but I am struggling to obtain the R2 change, F, and p values for each separate part. As you know SPSS gives a p value for the change in R2 when you add your new variable(s), so this is what I am hoping to get. If you are able to help in any way please let me know, thank you!
@Geoff1 I don't know how you have chosen to code the sequential regressions, but here is a sample using sashelp.cars. For nominal vars like TYPE and ORIGIN it makes groups of dummy vars. Dummies for a nominal var are added as a group in the regression model (minus a dummy for the reference value).
data have;
set sashelp.cars;
orig_asia=(origin='Asia');
orig_europe=(origin='Europe');
orig_usa=(origin='USA');
type_hybrid=(type='Hybrid');
type_suv=(type='SUV');
type_sedan=(type='Sedan');
type_sports=(type='Sports');
type_truck=(type='Truck');
type_wagon=(type='Wagon');
run;
proc reg data=have (drop=orig_usa type_sedan)
plots=none noprint outest=rsq_data rsquare;
var mpg_highway weight horsepower cylinders orig_: type_: ;
model mpg_highway=weight;
run ;
model mpg_highway=weight orig_: ;
run ;
model mpg_highway=weight orig_: horsepower ;
run ;
model mpg_highway=weight orig_: horsepower type_: ;
run ;
quit;
data rsq_extended;
set rsq_data;
delta_rsq=dif(_rsq_);
delta_indvars=dif(_in_);
run;
@mkeintz Thanks for the codes. I am also working on an analysis using sequential regression. And I am trying to obtain the significance of change in R square and significance of ANOVA tests between models. May I know if there is specific code that you use to obtain the significance of the sequential models?
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