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- Given only two categories in the
dependent variable, both methods produce similar
results.
- Binary logistic regression
has one major advantage: it produces very helpful
plots.
- Discriminant analysis
offers a potential advantage: it classified ungrouped
cases.
- SPSS says: "The functions are
generated from a sample of cases for which group
membership is known; the functions can then be
applied to new cases with measurements for the
predictor variables but unknown group
membership."
- Depending on the research
problem, this may be more or less of an
advantage.
- Given more than two categories in the
dependent variable, binary logistic regression cannot be
use.
- Multinomial logistic
regression replaces binary logistic in this
situation.
- However, the multinomial logistic
analysis uses a different approach that does not
generate plots.
- This is where discriminant
analysis offers more advantages:
- It generates helpful plots,
especially a territorial map, to aid
analysis.
- It still offers the opportunity
for classifying cases that are "ungrouped" on the
dependent variable.
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