Discriminant function analysis: Difference between revisions
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'''Discriminant function analysis''' involves the predicting of a categorical dependent variable by one or more continuous or binary independent variables. It is statistically the opposite of [[MANOVA]]. It is useful in determining whether a set of variables is effective in predicting category membership. <br /> |
'''Discriminant function analysis''' involves the predicting of a categorical dependent variable by one or more continuous or binary independent variables. It is statistically the opposite of [[MANOVA]]. It is useful in determining whether a set of variables is effective in predicting category membership. <br /> |
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It is also a useful follow-up procedure to a MANOVA. Instead of doing a series of one-way [[Analysis of variance|ANOVA]]s, for ascertaining how the groups differ on the composite of dependent variables. |
It is also a useful follow-up procedure to a MANOVA. Instead of doing a series of one-way [[Analysis of variance|ANOVA]]s, for ascertaining how the groups differ on the composite of dependent variables. |
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Revision as of 00:09, 4 February 2009
Discriminant function analysis involves the predicting of a categorical dependent variable by one or more continuous or binary independent variables. It is statistically the opposite of MANOVA. It is useful in determining whether a set of variables is effective in predicting category membership.
It is also a useful follow-up procedure to a MANOVA. Instead of doing a series of one-way ANOVAs, for ascertaining how the groups differ on the composite of dependent variables.
See also
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External links
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