Deck 9: Exploratory Factor Analysis

Question 1

What type of evidence is exploratory factor analysis often used to determine?

A) consequential validity
B) construct validity
C) criterion validity
D) reliability

Answer 1

B
Explanation: What exploratory factor analysis allows us to do is to work with all variables simultaneously, but at the same time know something about their underlying data structure. Exploratory factor analysis is therefore often used to provide evidence of construct validity.

Question 2

Finding which one of the following types of variance is the goal of exploratory factor analysis?

A) common variance
B) error variance
C) specific variance
D) total variance

Answer 2

A
Explanation: The underlying focus of factor analysis deals with finding common variance (distributed among the factors) and eliminating the unique variance that is not of interest (where total variance = common variance + specific variance + error variance).

Question 3

Exploratory factor analysis is also sometimes known as which one of the following?

A) component factor analysis
B) common factor analysis
C) principal components analysis
D) confirmatory factor analysis

Answer 3

B
Explanation: Exploratory factor analysis, EFA, is sometimes known as 'common factor analysis.'

Question 4

If your goal is only data reduction, which one of the following should be applied to your data?

A) confirmatory factor analysis
B) exploratory factor analysis
C) principal components analysis
D) structural equation modeling

Question 5

Which one of the following would be variables with the most appropriate measurement scales for conventional factor analysis?

A) 10 items related to employability that are measured on a three-point Likert scale
B) 10 test items which are each coded as correct or incorrect
C) 15 subscales which are each measured on a scale of 0-25
D) 20 satisfaction items, each coded as yes or no

Question 6

Which one of the following may arise when using binary data in conventional factor analysis?

A) factors are easier to interpret
B) factor solution with too few factors
C) the assumption of linearity will always be met
D) variables with similar splits will correlate even if the context of correlation doesn't make sense

Question 7

A researcher wishes to determine the factor structure of 20 continuous items and identify substantive meaning for those factors, for which existing theory for determining the relationships between variables is minimal. Which one of the following procedures is more appropriate?

A) confirmatory factor analysis
B) exploratory factor analysis
C) principal components analysis
D) structural equation modeling

Question 8

Outlying variables can be determined by which one of the following?

A) critical values for hypothesis test for a single multivariate outlier using Mahalanobis distance
B) largest squared and plot of squared Mahalanobis distance
C) multivariate normality omnibus test
D) weak correlations with the factors that are identified in the factor analytic model

Question 9

Which one of the following factor loadings would lead to a recommendation to discard a variable in a factor?

A) 0.1
B) 0.3
C) 0.5
D) 0.8

Question 10

Which one of the following factor loadings would lead to a recommendation to discard a variable in a factor?

A) bivariate scatterplots that suggest a linear relationship between variables
B) R squared values, computed from a regression model for an individual variable where that variable is the dependent variable and all remaining variables are the independent variables, which are near zero
C) statistically significant Mahalanobis distance scores
D) units that have been randomly sampled from a population