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yoyotort
Calcite | Level 5

I've attached the excel sheets. I created the smaller list to try evening out the number of variables in each column and make things more manageable. When I use it with this code I don't get any p values or F value and the degrees of freedom for each variable displays zero. 

proc anova data=cpi;
	class CPIAllMinusFnE2 CPIFood2 CPIEnergy2 CPIMedical2 CPIShelter2;
	model MinWageCPI2= CPIAllMinusFnE2 CPIFood2 CPIEnergy2 CPIMedical2 CPIShelter2;
run;


proc glm data=cpi;
 class CPIAllMinusFnE2 CPIFood2 CPIEnergy2 CPIMedical2 CPIShelter2;
 model MinWageCPI2= CPIAllMinusFnE2 CPIFood2 CPIEnergy2 CPIMedical2 CPIShelter2 ;
 output out=diag r=res p=pred;
run;

I'm using SAS Studio.

 

288dc2776e4b89e622131c789d479b09.pngdc0a77c16687c5104e96eade02d73c8b.png

4 REPLIES 4
PaigeMiller
Diamond | Level 26

First, avoid PROC ANOVA as I seriously doubt it is appropriate for such a model.

 

Show us the output from PROC GLM that concerns you, by pasting it into your reply. Many of us will not download Microsoft Office documents as they are security threats.

--
Paige Miller
yoyotort
Calcite | Level 5
I added pics of glm output, the difference between the data is size and the one with more variables doesn't have equal number of variables in each column.
Reeza
Super User

Show the log please.

data_null__
Jade | Level 19

Your right hand side doesn't look like CLASS variables.  Remove CLASS statement.

 

Capture.PNG

 

options ls=max center=0;
data cpi;
   infile cards dsd firstobs=2;
   input CPIAll2 CPIAllMinusFnE2 CPIFood2 CPIEnergy2 CPIMedical2 CPIShelter2 MinWageCPI2;
   cards;
CPIAll2,CPIAllMinusFnE2,CPIFood2,CPIEnergy2,CPIMedical2,CPIShelter2,MinWageCPI2
28.09,28.93,28.93,21.48,19.68,23.96,29.85
28.86,29.59,30.17,21.53,20.63,24.47,29.85
29.15,30.18,29.66,21.90,21.49,24.73,29.85
29.58,30.64,30.02,22.43,22.25,25.23,29.85
29.89,30.98,30.36,22.49,22.93,25.45,31.34
30.25,31.41,30.63,22.58,23.53,25.73,34.33
30.63,31.80,31.07,22.63,24.09,26.07,35.32
31.02,32.28,31.48,22.53,24.58,26.50,37.31
31.51,32.74,32.18,22.95,25.18,26.99,37.31
32.46,33.54,33.81,23.30,26.30,27.80,37.31
33.36,34.71,34.06,23.84,28.15,28.77,41.42
34.78,36.32,35.29,24.19,29.86,30.13,47.26
36.68,38.43,37.11,24.82,31.93,32.58,47.76
38.83,40.83,39.20,25.50,33.95,35.54,47.76
40.49,42.74,40.35,26.51,36.15,37.03,47.76
41.82,44.05,42.09,27.24,37.32,38.68,47.76
44.40,45.58,48.18,29.45,38.76,40.48,47.76
49.31,49.34,55.12,38.05,42.37,44.41,55.72
53.82,53.89,59.79,42.09,47.48,48.79,62.69
56.91,57.43,61.63,45.11,51.99,51.48,68.66
60.61,61.03,65.52,49.39,56.96,54.95,68.66
65.23,65.48,72.06,52.53,61.77,60.49,79.10
72.58,71.86,79.92,65.74,67.48,68.90,86.57
82.41,80.78,86.78,86.03,74.88,80.99,92.54
90.93,89.24,93.56,97.72,82.93,90.48,100.00
96.50,95.85,97.35,99.15,92.55,96.89,100.00
99.60,99.62,99.41,99.93,100.59,99.13,100.00
103.88,104.54,103.23,100.93,106.86,103.99,100.00
107.57,109.12,105.57,101.63,113.52,109.82,100.00
109.61,113.53,108.94,88.23,122.04,115.83,100.00
113.63,118.20,113.48,88.58,130.14,121.24,100.00
118.26,123.42,118.18,89.25,138.64,127.08,100.00
123.97,128.98,125.08,94.32,149.25,132.83,100.00
130.66,135.46,132.37,102.09,162.80,139.98,110.07
136.19,142.11,136.25,102.45,177.02,146.28,123.51
140.32,147.31,137.89,103.00,190.07,151.19,126.87
144.46,152.18,140.86,104.15,201.41,155.73,126.87
148.23,156.52,144.28,104.63,211.02,160.53,126.87
152.38,161.20,148.42,105.24,220.47,165.68,126.87
156.85,165.56,153.28,110.13,228.23,171.03,130.60
160.52,169.51,157.28,111.52,234.58,176.28,145.77
163.01,173.38,160.68,102.88,242.13,182.11,153.73
166.58,176.98,164.10,106.62,250.58,187.26,153.73
172.20,181.29,167.82,124.61,260.75,193.35,153.73
177.07,186.13,173.08,129.29,272.76,200.56,153.73
179.88,190.45,176.22,121.68,285.60,208.09,153.73
183.96,193.23,179.98,136.49,297.08,213.12,153.73
188.88,196.63,186.18,151.39,310.13,218.84,153.73
195.29,200.89,190.73,177.05,323.23,224.43,153.73
201.59,205.92,195.18,196.86,336.18,232.13,153.73
207.34,210.73,202.92,207.72,351.05,240.61,164.18
215.30,215.57,214.11,236.67,364.06,246.67,185.07
214.54,219.24,217.96,193.13,375.61,249.35,205.97
218.06,221.34,219.63,211.45,388.44,248.40,216.42
224.94,225.01,227.84,243.91,400.26,251.65,216.42
229.59,229.76,233.78,246.08,414.92,257.08,216.42
232.96,233.81,237.04,244.41,425.13,263.06,216.42
236.74,237.90,242.72,243.58,435.29,270.51,216.42
237.02,242.25,247.23,202.90,446.75,278.80,216.42
240.01,247.60,247.93,189.53,463.67,288.23,216.42
245.12,252.17,250.06,204.54,475.32,297.80,216.42
251.11,257.57,253.56,219.94,484.71,307.66,216.42
255.66,263.21,258.32,215.29,498.41,318.05,216.42
;;;;
   run;

proc print width=min;
   run;
proc glm data=cpi;
   model MinWageCPI2=CPIAllMinusFnE2 CPIFood2 CPIEnergy2 CPIMedical2 CPIShelter2 / solution;
   run;

 

 

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