Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Psyc 2014 > Factor Analysis > Flashcards

Factor Analysis Flashcards

1
Q

Who invented factor analysis and why?

A

-Spearman, as a way to uncover ‘g’ factor

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is the definition of factor analysis?

A
  • an umbrella term to cover a variety of multivariate statistical techniques to uncover the latent dimensions from a set of observed attributes.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What is factor analysis used for?

A
  • to condense a large group of observed attributes into a much smaller set of constructs (factors/components)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

The dimensions should be a linear combination of observed attributes. T/F

A
  • true, should be, although modern developments allow for non-linear combinations
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What allows for the dimensions/factors/combinations to be linear?

A
  • the observed attributes must be numerical or possess an underlying continuous structure.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Is there a need to define causal independent/dependent variables in factor analysis?

A
  • no, because FA is not assessing causal relationships

- attempts to maximise the attributes’ explanatory power than predictive power.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What are the major FA types?

A
  • EFA (EXPLORATORY FACTOR ANALYSIS)
  • PCA (PRINCIPAL COMPONENTS ANALYSIS)
  • CFA (CONFIRMATORY FACTOR ANALYSIS)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What does EFA attempt to do?

A
  • IDENTIFYING A HIDDEN STRUCTURE/CONSTRUCT

- almost any construct you know in psychology was empirically investigated through this approach

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

How does FA often violate the ‘numerical rule’ of linearity?

A
  • often use likert scales which are ORDINAL SCALES
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What does PCA attempt to do?

A
  • the simplest type of EFA
  • assumes ALL variance in the items can be explained by some hidden structure/construct.
    ie. big assumption, therefore perhaps erroneous
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What does confirmatory factor analysis attempt to do?

A
  • looking to CONFIRM an already hypothesised, theorised or empirically identified structure/construct.
  • also might use when we are looking to replicate an already done study
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is an item in FA?

A
  • observed element of an attribute e.g. question in a questionnaire
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is factorability?

A
  • the suitability of an items to be included in an FA model

- depends on numerical association between items –> items below 0.5 or above 0.9 need to be considered carefully

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is Bartlett’s test of sphericity?

A
  • tests whether the item correlation matrix is significantly different from a matrix with ZERO CORRELATIONS (testing the factorability of a dataset)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What is simple structure?

A
  • refers to the situation where items form distinct groups based on the degree of their associations i.e. items form highly independent dimensions
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What do we need for a factor to be meaningful?

A
  • factors need to be related both in a QUALITATIVE (CONCEPTUAL) AND QUALITATIVE (NUMERICAL) SENSE
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What are orthogonal factors or components?

A
  • factors that are considered to be independent from each other e.g. trait theory, neuroticism and extraversion
18
Q

What are oblique factors/components?

A
  • considered to be related to a degree to each other e.g. the Gf and Gc are not constructed to be independent.
19
Q

What is factor loading?

A
  • the correlation between an item and a factor (usually >0.4 to be considered to belong to that factor.
20
Q

what is rotation in a geometric space?

A
  • the geometric transformation of the factors in order to generate a model that contains a SIMPLE STRUCTURE
21
Q

When is varimax rotation used?

A
  • it is used to rotate orthogonal (unrelated/independent) factors in such a way that maximises the variance each of them explains
22
Q

What is the Kaiser criterion?

A
  • retain any factor that has an eigenvalue >/= 1
23
Q

What is Cattell’s scree plot rule

A
  • retain factors which do not form part of the ‘elbow’ –> i.e. that are on the steep slope
24
Q

What is the variance explain rule?

A
  • retain all factors that can collectively account for 80-90% of the total variance
25
Q

What is the Joliffe criterion?

A
  • retain all factors with eigenvalues greater than or equal to 0.70
26
Q

What is the comprehensibility rule?

A
  • retain all factors that are MEANINGFUL and CLEARLY interpretable within the context of a given study (final assessment rests on psychological knowledge- FA cannot name the factors for us)
27
Q

What can Cronbach’s alpha be considered an index of?

A
  • internal consistency reliability

- internal consistency validity

28
Q

By assessing parallel-forms reliability what else are we assessing?

A
  • concurrent validity

- convergence validity

29
Q

What is inter-rater reliability closely related to?

A
  • content validity
30
Q

What can test-retest reliability (measured over time) be used as an index of?

A
  • external validity
31
Q

How can we allow for sufficient variability of items and participants?

A
  • inversely keyed items and homogenous items
  • minimisation of serial effects
  • examine invariable responses closely
  • item difficulty or clarity
  • ceiling/floor effects
32
Q

What is the problem with constant measurements?

A
  • they cannot really be statistically analysed.

- data analysis cannot always account for fix design errors

33
Q

What is a frame error?

A
  • errors in the sampling (Q analysis)- we sampled ppl that don’t belong
34
Q

What is domain error?

A
  • errors in the domain we sampled
35
Q

What are some errors in samples?

A
  • nonresponse/participant errors
36
Q

What are some errors with observed/true scores?

A
  • measurement error
37
Q

What is generalizability theory?

A
  • it adds systematic error in the observed scores and attempts to map it and eliminate it (ie. control it)
38
Q

What is item response theory?

A
  • mathematically maps the difficulty of measurement items and maps them against participants’ ability on a construct
  • can be used to make predictions
39
Q

What are the uses of profiling?

A
  • criminal personality profiling: eliminating suspects, identify unknown offenders, used with unusal crimes, adaptive interrogation techniques
40
Q

What are the uses of psychography, psychobiography & psychohistory?

A
  • identify and explain issues and themes throughout a person’s life from a psychological perspective

Psyc 2014 (12 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions