Factor analysis in general

Question 1

How does EFA achieves parsimony solutions?

Answer 1

by explaining the maximum amount of variance in the correlation matrix by using the smallest amount of explanatory constructs.

Question 2

What is PCA concerned with ?

Answer 2

concerned only with establishing which linear components exist within the data and how a particular variable might contribute to that component

Question 3

what a fundamental advantage that CFA has over EFA

Answer 3

it can control every aspect of the model specifications.

Question 4

CFA offers a very strong analytic framework for evaluating the equivalence of measurement models across distinct groups

True or False

Answer 4

True

Question 5

what are changes in the EFA that doesnt affect the results

Answer 5

erasing a participant missing data and reverse scoring.

Question 6

‣ How can we use data to help decide whether we have a General Factor
of Personality here or not?

Answer 6

1. The one overall factor must account for a “great” amount of
   variance
2. Any other factors after the first one should be more marginal
3. The OCEAN subscales must relate strongly to the Big One

Question 7

what does standardized mean ?

Answer 7

first definition: you transform your data into z-scores

second definition:
Controlled administration conditions, normative
information available, interpretation guidelines available, instruction
manual available, carefully vetted (?), and probably costly