Discriminant Analysis - Statpower

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Classification Function Coefficients INFO SIMILAR ARITH PICCOMPL (Constant) SENILE 0 1 .760 .734 -.239 -.447 .491 .483 .811 .366 -10.382 -5.632 Fisher's linear discriminant functions To perform classification, you compute the two functions, and assign an individual to the group with the higher score.
Now, if we drop the two non-contributing variables and redo the analysis, we get Original Count % Classification Results a SENILE 0 1 0 1 Predicted Group Membership 0 1 Total 29 8 37 4 8 12 78.4 21.6 100.0 33.3 66.7 100.0 a. 75.5% of original grouped cases correctly classified. Exactly the same as before.
Page 1 and 2: Discriminant Analysis In discrimina
Page 3 and 4: Linear Discriminant Function - Two
Page 5 and 6: The linear discriminant function wa
Page 7 and 8: ( ) βˆ = cA −1 x −x (3) 1 2 w
Page 9 and 10: Recall that group 1 is associated w
Page 11 and 12: so ˆβ in Equation (9) can be repl
Page 13 and 14: Of course, we could generate a diff
Page 15 and 16: above function values will lead to
Page 17 and 18: Example. Morrison (1990, page 143)
Page 19 and 20: In this case, −1 S is given by
Page 21 and 22: Note that variables x 1 and x 3 do
Page 23: But first, let’s perform the anal

Discriminant Analysis - Statpower

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