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Psyc 207 > seminar 2 factor analysis > Flashcards

seminar 2 factor analysis Flashcards

1
Q

What is factor analysis?

A

A statistical method which looks at how lots of different items correlate and determines how many theoretical constructs could most simply explain what you see.

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2
Q

What is principle component analysis?

A

Very similar to factor analysis, we conduct PCA rather than FA as it is less complex and is psychometrically sound

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3
Q

What are the differences between Factor Analysis and Principle component analysis?

A

FA uses a mathematical model from which the factors are estimated
PCA uses the original data to derive the set of clusters of variables

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4
Q

What does factor analysis do?

A
  • Helps us determine items/behaviours relating to constructs
  • Takes info and simplifies it by placing it into factors
  • Examines the pattern/
    correlations between variables to calculate new variables (super variables or FACTORS)
  • Determining the maximum amount of common variance using the smallest amount of explanatory constructs
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5
Q

What are the uses of FA?

A
  • Understanding the structure of an underlying dimension/ construct
  • to construct a questionnaire
  • to reduce a data set to a more manageable and purposeful size.
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6
Q

How can factor analysis help with questionnaires

A

Can determine which behaviours add up to a personality trait.

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7
Q

What can we infer by looking at the correlation between scale items?

A

Something about their underlying nature (theoretical constructs)

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8
Q

What causes increase chance of a type 1 error?

A

More correlations- so we don’t just use a correlation matrix

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9
Q

How do you conduct factor analysis?

A
  1. input the data into spss
  2. conduct FA (PCA)
  3. check assumptions
  4. How many factors? (Eigenvalues and scree plot)
  5. Re-analyse with rotation
  6. Interpret factors
  7. factor scores
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10
Q

What is the correct way to input data in spss for fa?

A

A score should be supplied for each question, opposed to an overall score

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11
Q

How do you conduct FA in spss?

A
  • > Analyze
  • > dimension reduction
  • > factor
  • > Select descriptives, univariate and first column of correlation matrix
  • > select extraction and then scree plot
  • > options: sorted by size and suppress small coefficients, change value to .40
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12
Q

What is the Barlett’s test?

A

Measures whether the correlation matrix differs from any identity matrix and therefore, should be significant

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13
Q

What is the KMO test?

A

Indicates if there is a distinct and reliable set of factors from the patterns of correlations between variable- this will lie between 0-1, look for a value closer to 1.

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14
Q

What is the eigenvalue?

A

The variance accounted for by that factor. Commonly, only factors of eigenvalues above 1 should be considered.

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15
Q

What is Kaiser criterion?

A

Eigenvalues

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16
Q

Why should kaiser be used with caution?

A

Criterion is accurate with less than 30 variables and communalities >.70

17
Q

What does a scree plot do?

A

Lists factors in order of eigenvalues.

18
Q

What is the cut off point of a scree plot?

A

The point of inflexion (where the point of the line changes/ flattens)

19
Q

Why are un-rotated factors difficult to interpret?

A

1- factors correlate with many variables

2- variables load onto many factors

20
Q

What does rotation do?

A

Maximises loading of each variable on to one of the extracted factors and minimises loadings on the other

21
Q

What are the different types of rotation?

A

Orthogonal

Oblique

22
Q

What is orthogonal rotation?

A

We do not assume out factors to correlate. Varimax, Quartimax, Equamax

23
Q

Which type of orthogonal rotation did we use and why?

A

Varimax which minimises the humber of high loadings on a factor and maximises the difference between dimensions.

24
Q

What is oblique rotation?

A

We assume our factors to correlate (good theoretical evidence suggesting so). Oblimin, Promax.

25
Q

How do you add rotation in spss?

A

Rotation, varimax

26
Q

What does the output in spss show for the rotated component matrix?

A

Factor loadings

27
Q

What happens if items are loading onto more than 1 factor?

A

Look at where it loads more strongly, if there is a difference of more than .2 between then we take it that the larger is stronger.

28
Q

What happens if you have a negative item?

A

Look at where it is loading more strongly

29
Q

What does rotation do?

A

Aids interpretation and loadings

30
Q

What are factor scores?

A

Sum of scores and reversing negative scores.

31
Q

How do you extract factors?

A

Scree plot and Kaiser’s criterion

32
Q

What are factor scores?

A

Sum of scores and reversign negative scores

Psyc 207 (2 decks)

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