I'm having the same problem, but I'm already using proc glm. proc glm data = cross; model tern_co tern_cr col_L col_a col_b pH hume intra_fat rendi = sexo edad musc; class = sexo, edad, musc; Can I only put one variable for class? I really don't get what's wrong with it. Here's the whole code: data cross;
infile datalines dlm='09'x;
input sexo$ edad$ musc$ tern_co tern_cr col_L col_a col_b pH hume intra_fat rendi;
cards;
c 1 LD 4.00 1.20 28.47 19.34 17.22 5.64 73.09 1.49 51.65
c 1 LM 3.60 1.50 47.90 13.02 17.87 5.48 71.62 1.88 51.65
c 1 LD 3.90 1.20 29.57 20.11 16.55 5.49 70.33 3.94 53.16
c 1 LM 4.40 1.40 42.41 16.10 17.13 5.38 74.29 2.25 53.16
c 1 LD 6.40 1.30 33.67 13.82 10.52 5.66 70.33 3.94 51.14
c 1 LM 3.50 3.10 51.67 11.48 15.29 5.62 74.29 2.25 51.14
c 2 LD 4.00 0.80 32.35 21.36 19.52 5.51 72.44 2.32 52.56
c 2 LM 2.80 1.70 41.68 17.34 18.90 5.42 74.09 1.77 52.56
c 2 LD 2.80 1.70 34.40 15.96 11.63 5.42 72.53 2.71 51.39
c 2 LM 3.00 1.80 43.85 15.23 14.98 5.43 67.65 0.62 51.39
c 2 LD 4.20 2.10 37.96 15.01 11.91 5.61 73.74 1.35 52.38
c 2 LM 2.40 0.80 48.28 13.37 15.36 5.58 76.92 0.52 52.38
c 2 LD 2.60 1.10 36.98 20.32 19.54 5.40 71.99 3.94 51.16
c 2 LM 3.70 2.10 46.82 16.23 19.29 5.50 74.18 2.27 51.16
c 3 LD 3.80 1.10 33.16 15.43 11.33 5.97 72.59 2.72 46.08
c 3 LM 5.00 2.80 42.88 16.69 15.50 5.80 72.28 2.80 46.08
c 3 LD 5.00 1.20 34.05 16.38 11.67 5.94 69.29 3.01 53.26
c 3 LM 4.50 1.50 45.51 16.17 15.48 5.84 75.85 2.38 53.26
c 3 LD 7.70 0.60 33.44 17.43 12.74 5.96 72.81 2.74 53.25
c 3 LM 5.60 1.80 39.77 18.77 16.32 5.67 70.98 3.54 53.25
c 3 LD 6.80 1.00 33.95 15.53 11.65 5.71 75.52 2.69 50.51
c 3 LM 4.60 2.00 45.97 16.00 16.85 5.78 76.03 1.80 50.51
c 3 LD 8.20 0.90 33.79 18.33 19.79 5.90 73.31 3.23 54.61
c 3 LM 8.60 1.30 42.51 18.53 16.88 5.62 70.80 2.90 54.61
c 3 LD 7.70 5.60 33.44 17.43 12.74 5.34 72.81 2.74 51.99
c 3 LM 0.60 1.80 39.77 18.77 16.32 5.67 70.98 3.54 51.99
c 3 LD 0.90 3.90 32.26 17.96 13.32 5.66 69.66 5.35 50.97
i 3 LM 1.70 3.80 42.48 16.66 15.73 5.62 70.06 1.80 50.97
i 1 LD 4.90 1.40 29.33 20.27 17.91 5.60 72.15 1.37 53.79
i 1 LM 3.30 2.00 44.92 15.46 17.80 5.13 74.60 1.47 53.79
i 1 LD 2.60 1.60 33.22 18.53 17.29 5.55 71.58 2.17 52.71
i 1 LM 3.60 1.60 44.38 14.74 17.66 5.53 75.81 0.98 52.71
i 1 LD 5.20 1.20 38.74 17.49 15.40 5.47 74.88 0.99 55.05
i 1 LM 3.90 1.40 47.97 12.14 14.44 5.51 73.09 2.32 55.05
i 1 LD 4.50 1.30 36.49 15.43 12.05 5.49 72.73 1.69 52.44
i 1 LM 4.10 4.10 44.86 14.32 14.64 5.43 74.23 0.89 52.44
i 2 LD 7.40 1.00 35.84 21.48 19.73 5.52 71.47 3.10 48.01
i 2 LM 3.10 3.20 42.18 15.83 18.07 5.66 73.12 0.89 48.01
i 2 LD 4.70 3.20 32.12 16.24 11.50 5.54 70.20 2.06 56.11
i 2 LM 3.50 1.70 39.48 15.74 13.24 5.80 74.94 0.69 56.11
i 2 LD 1.60 1.60 27.52 12.71 11.48 5.57 72.79 2.00 52.04
i 2 LM 2.20 2.00 32.95 12.72 15.71 5.29 73.67 1.19 52.04
i 2 LD 6.60 1.80 31.88 18.85 12.78 5.47 74.86 1.13 51.90
i 2 LM 1.70 2.10 43.81 12.96 13.28 6.26 72.62 1.99 51.90
i 2 LD 4.20 1.20 33.35 15.53 11.08 5.94 75.22 1.06 55.94
i 2 LM 3.70 1.70 44.54 12.78 13.52 5.93 72.44 3.62 55.94
i 3 LD 9.60 1.30 30.95 15.13 11.43 5.92 76.41 0.48 52.74
i 3 LM 4.40 3.40 37.87 14.27 12.79 5.75 76.43 0.64 52.74
i 3 LD 6.50 1.20 33.78 18.41 13.29 6.78 75.11 1.17 56.79
i 3 LM 5.20 1.50 41.18 16.67 14.65 5.89 76.52 1.17 56.79
i 3 LD 5.80 1.20 32.89 16.03 11.48 5.87 75.46 1.20 57.22
i 3 LM 8.50 2.20 46.38 15.79 15.71 5.85 74.35 1.32 57.22
i 3 LD 5.90 0.90 30.26 15.53 10.17 5.95 73.92 1.44 56.84
i 3 LM 6.60 2.30 36.56 14.05 11.12 5.89 74.46 0.92 56.84
i 3 LD 8.50 1.30 30.27 14.22 19.76 5.22 76.41 0.48 57.32
i 3 LM 5.10 3.40 40.15 16.14 13.27 5.45 76.43 0.64 57.32
i 3 LD 7.30 0.90 33.28 15.78 10.61 5.41 74.69 1.69 53.36
i 3 LM 4.90 1.60 43.02 16.74 15.99 5.61 75.79 0.64 53.36
i 3 LD 9.70 1.10 31.73 14.19 10.61 5.86 73.94 1.90 49.49
i 3 LM 4.40 1.70 38.97 19.47 16.52 5.80 67.65 0.62 49.49
;
proc glm data = cross;
model tern_co tern_cr col_L col_a col_b pH hume intra_fat rendi = sexo edad musc;
class = sexo, edad, musc; And here's the log: OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
72
73
74
75
76 data cross;
77 infile datalines dlm='09'x;
78 input sexo$ edad$ musc$ tern_co tern_cr col_L col_a col_b pH hume intra_fat rendi;
79
80 cards;
NOTE: LOST CARD.
RULE: ----+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0
143 ;
sexo= edad= musc= tern_co=. tern_cr=. col_L=. col_a=. col_b=. pH=. hume=. intra_fat=. rendi=. _ERROR_=1 _N_=61
NOTE: SAS went to a new line when INPUT statement reached past the end of a line.
NOTE: The data set WORK.CROSS has 60 observations and 12 variables.
NOTE: DATA statement used (Total process time):
real time 0.01 seconds
cpu time 0.02 seconds
143 ;
144 proc glm data = cross;
145
146 model tern_co tern_cr col_L col_a col_b pH hume intra_fat rendi = sexo edad musc;
ERROR: Variable sexo should be either numeric or specified in the CLASS statement.
NOTE: The previous statement has been deleted.
147 class = sexo, edad, musc;
_____
180
NOTE: The previous statement has been deleted.
ERROR 180-322: Statement is not valid or it is used out of proper order.
148
149 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;
162
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