annotating missing part of the output from multiple regression PROC GLM

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Contributor
Posts: 61

annotating missing part of the output from multiple regression PROC GLM

hi,

My name is Chang. I have run a linear regression on the relationship between a single dependent and several predictors. I have saved the output as a html. As shown in this output, this analysis produced missing values from some source variables, such as day_temp_diff in type I SS, type III SS and in the parameter estimate table. Can any one please advice on how to annotate the missing values? My gut feeling is that these variables should be removed from my linear model. But I would like to know why there are missing values there. Any comments will be highly appreciated. My codes as below. There are no error message from them. Tassui

%let suffix1= ED;

proc sort data= ED_wide_b out= ED_wide_c;

     by day_type_cat;

run;

proc glm data= ED_wide_c;

    class day_type_cat;

    model day_EDvolume= day_type_cat day_high_temp day_low_temp day_temp_diff day_mean_temp diff_meanDayTemp diff_meanDayRH day_RH_percen day_RH_diff day_high_RH/ solution;

    ods output ParameterEstimates=    _reg01_dPara_&suffix1.;

    ods output NObs=                _reg02_dNum_&suffix1.;

    ods output FitStatistics=        _reg03_dRsq_&suffix1.;

run;

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Super User
Posts: 11,343

Re: annotating missing part of the output from multiple regression PROC GLM

Have you run any diagnostics on the data such as Proc freq or univariate for the variables in question?

Also, if day_temp_diff = day_high_temp - day_low_temp then since it is determined by two other variables it likely isn't going to contribute anything to the model.

Respected Advisor
Posts: 2,655

Re: annotating missing part of the output from multiple regression PROC GLM

hit on why there is no estimate.  If the diff is completely dependent on the other two variables, and all are included in the model, the sweep operator will eliminate the redundant variable and set the estimate to missing.

Steve Denham

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