Discriminant Analysis - Statpower

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Using all 4 variables, we get the following: 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. In this case, the misclassification rates are rather high. Moreover, these classification rates are probably unduly optimistic. We can improve things.
But first, let’s perform the analysis using the more general approach employed by SPSS. SPSS can report a linear discriminant function for each group, as in Equations (14)–(15).
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: Note that variables x 1 and x 3 do
Page 25 and 26: Now, if we drop the two non-contrib

Discriminant Analysis - Statpower

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