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13 Cards in this Set
- Front
- Back
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Reasons for utilizing multivariate techniques
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1)Gathering additional information about a specific bivariate relationship by using another variable.
2)Multivariate statistical techniques cannot prove causation, but can provide evidence. |
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Z variable
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Third variable that is controlled to see the relationship between X and Y.
If the control variable has an effect, the relationship between X and Y will change under various conditions of Z. |
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Partial Tables
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Tables that are split according to the categories of the Z variable.
This controls for the effect of Z. |
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Elaboration
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A more detailed form of multivariate analysis.
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Level of measurement for multivariate analysis
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Nominal and ordinal
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Direct Relationships
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The relationship between X and Y are the same in all partial tables and the bivariate tables.
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Spurious or intervening relationships
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The relationship between X and Y is the same in all partial tables, but much weaker than in the bivariate table.
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Interaction
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Each partial table and the bivariate table show different relationships between X and Y.
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Outcome of a Direct Relationship
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Z has no effect on the relationship between X and Y and can be ignored.
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Outcome of a Spurious Relationship
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Z occurs before both X and Y in time and is a common cause of both X and Y.
Ignore X and focus on Y and Z. |
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Outcome of an Intervening Relationship
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X is causally linked to Z which is causally linked to Y
Continue to analyze all three variables. |
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Outcome of an Interaction
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Incorporate Z and analyze Z's subgroups separately.
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Partial Gamma
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Strength of Association between X and Y once Z has been removed
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