Factor Analysis

Question 1

How is Factor Analysis most commonly used

Answer 1

an exploratory approach:

• good to examine the structure within a large number of variables
• good to explain the nature of their relationships

Question 2

How is Factor Analysis used in a confirmatory manner

Answer 2

• used to verify the factor structure of a set of observed variables
• used to test the hypothesis that a relationship between observed variables and their underlying latent constructs exists

Question 3

Exploratory Factor Analysis is used to:

Answer 3

1. Explore possible underlying factor structure of a set of observed variables without imposing a predefined structure to the outcome
2. Identify the underlying factor structure
3. Describe and ID the # of factors

Question 4

Goals to EFA

Answer 4

determine the # of latent constructs underlying a set of variables

provide a means of explaining variation among variables using few new factors

define the content of meaning of factors

Question 5

Assumptions of EFA

Answer 5

continuous level of measurement with normal distribution

sample size should be large enough

correlation >0.3 between the variables

Question 6

Limitations of EFA

Answer 6

variables could be specific

non-normal distribution of data

sample size larger than required is desirable to accommodate for possible missing data

No casual interferences can be made from correlations alone

Question 7

Confirmatory Factor Analysis is used to:

Answer 7

Test the hypothesis that there exists a relationship between the observed variables and their underlying latent constructs

Question 8

Procedure of CFA

Answer 8

1. review the relevant theory and research literature to support model specification
2. specify a model
3. collect data
4. assess model fit by
   - hypothesis testing
   - fit indices look up

Question 9

Limitations of CFA

Answer 9

sample size must be large

multivariate normality

outliers

missing data

Question 10

Exploratory Factor Analysis:

Factor Loadings

Answer 10

the coefficient as a measure of the correlation between the individual variable and the overall factor

Question 11

Exploratory Factor Analysis:

Criteria for significance of Factor Loadings

Answer 11

FL>0.3: minimum consideration

FL>0.4: more important

FL>0.5: practically significant

Question 12

Exploratory Factor Analysis:

Extraction of Factors

Answer 12

Pull out only the components using a cutoff point where eigenvalue at least 1

Question 13

Exploratory Factor Analysis:

Rotation of Factors

Answer 13

Process of developing a unique statistical solution so that each variable relates highly to only one factor

Question 14

Exploratory Factor Analysis:

Naming Factors

Answer 14

Naming the factors assigned in Rotation of Factors

Question 15

Applications of Factor Analysis

Answer 15

Exploratory Analysis
Reduction of data
Factor scores
Construct Validity
Hypothesis Testing

Question 16

Limitations of Factor Analysis

Answer 16

Factors are hypothetical statistical concepts

Data may be organized differently by using different extraction or rotation methods that alter the factor’s meaning

Generated factors may be totally uninterpretable within the framework of the research question