Here is the Discriminant Function Analysis Done With SAS DATA 6 seckel; INFILE 'C:\Users\Vati\Documents\_XYZZY\_Stats\StatData\harass90.dat'; INPUT VERDICT $ 16 17 18 19 20 21 D_excit D_calm D_indep D_sincer D_warm D_attrac 22 23 24 25 26 D_kind D_intell D_strong D_sophis D_happy 28 29 30 31 32 33 P_excit P_calm P_indep P_sincer P_warm P_attrac 34 35 36 37 38; P_kind P_intell P_strong P_sophis P_happy 1; 2; If verdict = 'Y' then verdic = else verdic = PROC DISCRIM simple canonical listerr; CLASS verdict; VAR D_excit -- P_happy; PRIORS proportional; PROC REG; run; MODEL verdic = D_excit -- P_happy / stb; 2 GROUP DFA, Harass90 Study The DISCRIM Procedure Total Sample 145 DF Total 144 Size Variables 22 DF Within 143 Classes Classes 2 DF Between 1 Classes 145 Number of Observations Read 145 Number of Observations Used Class Level Information VERDICT Variable Frequency Weight Proportion Prior Name Probability N N 50 50.0000 0.344828 0.344828 Y 95 95.0000 0.655172 0.655172 Y The DISCRIM Procedure
Here is the Discriminant Function Analysis Done With SAS DATA seckel; INFILE 'C:\Users\Vati\Documents\_XYZZY\_Stats\StatData\harass90.dat'; INPUT VERDICT $ 6 D_excit 16 D_calm 17 D_indep 18 D_sincer 19 D_warm 20 D_attrac 21 D_kind 22 D_intell 23 D_strong 24 D_sophis 25 D_happy 26 P_excit 28 P_calm 29 P_indep 30 P_sincer 31 P_warm 32 P_attrac 33 P_kind 34 P_intell 35 P_strong 36 P_sophis 37 P_happy 38; If verdict = 'Y' then verdic = 1; else verdic = 2; PROC DISCRIM simple canonical listerr; CLASS verdict; VAR D_excit -- P_happy; PRIORS proportional; PROC REG; MODEL verdic = D_excit -- P_happy / stb; run; 2 GROUP DFA, Harass90 Study The DISCRIM Procedure Total Sample Size 145 DF Total 144 Variables 22 DF Within Classes 143 Classes 2 DF Between Classes 1 Number of Observations Read 145 Number of Observations Used 145 Class Level Information VERDICT Variable Name Frequency Weight Proportion Prior Probability N N 50 50.0000 0.344828 0.344828 Y Y 95 95.0000 0.655172 0.655172 The DISCRIM Procedure