10-26-2015 05:15 PM
proc glmselect data=data1;
class day weekday year ;
model percent_change = year| day | weekday dummy1 dummy2 dummy3 /
selection=backward slstay=0.10 details=all stats=all ;
output out=outdata predicted=p_expost residual=r_expost ;
ods output ParameterEstimates=paramest;
ods output off;
I am trying to make a model using the year (2007 through 2015), the day of the month (1 through 28-31), and weekday (1 through7), as well as dummy variables, by month (so effectively 12 seperate models, one for each month). I want to start with all of the interaction terms and then use backward selection to end with only the most significant. However, when I run the model above, I get the note 'The SLSTAY= option has no effect with the selected options.' and all of my standard error and t-value columns for parameter estimates are empty. Is there a maximum number of interaction terms you can enter into the model (I'm at 182 total), or is there a problem with my code?
Thanks in advance for the help!
10-26-2015 11:12 PM
If you want the traditional approach for selecting which effect will leave the model based on significance, you must add SELECT=SL to the model statement. By default, SELECT=SBC which is incompatible with SLSTAY=. Check the documentation.
The absence of standard errors is probably due to overparameterization, i.e. some parameters cannot be estimated because there isn't enough data to support all the year*day*weekday interactions. Try grouping some of your class levels to reduce their numbers, i.e. weekday -> (workday, weekend), day -> (start, middle, end) of the month.