Discriminant Analysis - Statpower

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The individual is classified into the group whose score is highest. In practice, prior probabilities are often not known, in which case the estimates pˆ j N j = (20) N • are often employed as a default.
Example. Morrison (1990, page 143) gives data for 49 subjects, 12 diagnosed with “senile factor present” and 37 diagnosed with “no senile factor.” The data are available online in the file morrisonEx43.sav. The Wechsler Adult Intelligence scale was administered to all subjects by independent investigators, and scores for 4 subtests (Information, Similarities, Arithmetic, Picture Completion) recorded. So the data set consists of 49 observations on 5 variables.
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: above function values will lead to
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 and 24: But first, let’s perform the anal
Page 25 and 26: Now, if we drop the two non-contrib

Discriminant Analysis - Statpower

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