Multivariate Techniques

Question 1

The term ____________________ is applied to a variety of techniques that are used to investigate the relationships among 3+ variables.

Answer 1

Multivariate technique.

Question 2

_____________________ are used when a distinction is made between independent and dependent variables (predictors and criteria) and the former will be used to predict or estimate status on the latter.

Answer 2

Dependence methods.

Question 3

_____________________ are used when a distinction is not made between independent and dependent variables and include several data reduction techniques.

Answer 3

Interdependence methods.

Question 4

______________________ is the appropriate multivariate technique when 2+ continuous or discrete predictors will be used to predict status on a single continuous criterion.

Answer 4

Multiple regression.

Question 5

The output of a multiple regression analysis is a ____________________ and a ______________________.

Answer 5

• Multiple correlation coefficient (R)
• Multiple regression equation

Question 6

The ___________________ indicates the degree of association between the criterion and a linear combination of predictors, and can be squared to obtain a measure of shared variability.

Answer 6

Multiple correlation coefficient (R).

Question 7

The _______________________ is an extension of the regression equation and permits prediction of a person’s score on the criterion based on a linear combination of his/her scores on two or more predictors.

Answer 7

Multiple regression equation.

Question 8

The ________________ of each predictor’s coefficient is determined by a combination of two factors - the magnitude of the correlation between the predictor and the criterion, and the magnitude of the correlation between the predictor and every other predictor.

Answer 8

Magnitude.

Question 9

High correlations between predictors is referred to as __________________________.

Answer 9

Multicollinearity.

Question 10

The most basic form of multiple regression is called _________________ regression, and entails analyzing the effects of all of the predictors on the criterion at once.

Answer 10

Simultaneous (simple) regression.

Question 11

______________ regression, one predictor is added in each subsequent analysis; in ______________ regression, one predictor is eliminated in each subsequent analysis.

Answer 11

• Forward stepwise regression
• Backward stepwise regression

Question 12

Multiple regression is often used instead of the __________, and is particularly useful when groups are unequal in size since this condition can reduce both the power and robustness; it is also useful when the IVs are measured on a continuous scale, because the __________ requires continuous IVs to be converted into categories; finally, it permits a researcher to add or subtract predictors to determine which subset of variables best explains variability in the DV.

Answer 12

ANOVA (both blanks).

Question 13

Whenever a multiple correlation coefficient and a multiple regression equation are _____________________ on another sample, the size of the correlation tends to __________.

Answer 13

• Cross-validated
• Shrink

Question 14

___________________ is an extension of multiple regression that is used when two or more continuous predictors are to be used to predict status on two or more continuous criteria.

Answer 14

Canonical correlation.

Question 15

_________________________ is the appropriate technique when two or more continuous predictors will be used to predict or estimate a person’s status on a single discrete (nominal) criterion. The accuracy of this is assessed by determining the _________, which is the proportion of cases that are correctly classified.

Answer 15

• Discriminant function analysis
• Hit rate

Question 16

_____________________ is used to predict status on a single discrete criterion using two or more continuous or discrete predictors. It assumes that the relationships are nonlinear.

Answer 16

Logistic regression.

Question 17

_________________ is a causal modeling technique, and can be considered an extension of multiple regression. It involves translating a theory about the causal relationships among a set of variables into a path diagram, collecting the data on hte variables, and using the data to derive path coefficients (regression coefficients) that indicate the direction and strength of the relationship beween pairs of variables.

Answer 17

Path analysis.

Question 18

__________________ is more complex than path analysis, and can be used when a causal model includes recursive (one-way) and non-recursive (two-way) paths.

Answer 18

LISREL (linear structural relations analysis).

Question 19

_____________________ involves simplifying a set of data by reducing a larger number of variables (e.g., tests or test items) to a smaller number of factors that explain the intercorrelations between those variables.

Answer 19

Factor analysis.

Question 20

_________________ is used to group people or objects into a smaller number of mutually exclusive and exhaustive subgroups (clusters) based on their similarities; it is used to identify, define, or confirm the nature and number of subgroups.

Answer 20

Cluster analysis.