R: 11 emotional variables from Burt (1915)

burt {psych} | R Documentation

## 11 emotional variables from Burt (1915)

### Description

Cyril Burt reported an early factor analysis with a circumplex structure of 11 emotional variables in 1915. 8 of these were subsequently used by Harman in his text on factor analysis. Unfortunately, it seems as if Burt made a mistake for the matrix is not positive definite. With one change from .87 to .81 the matrix is positive definite.

### Usage

    data(burt)

### Format

A correlation matrix based upon 172 "normal school age children aged 9-12".

Sociality

  Sociality

Sorrow

  Sorrow

Tenderness

  Tenderness

Joy

  Joy

Wonder

  Wonder

Elation

  Elation

Disgust

  Disgust

Anger

  Anger

Sex

  Sex

Fear

  Fear

Subjection

  Subjection

### Details

The Burt data set is interesting for several reasons. It seems to be an early example of the organizaton of emotions into an affective circumplex, a subset of it has been used for factor analysis examples (see `Harman.Burt`, and it is an example of how typos affect data. The original data matrix has one negative eigenvalue. With the replacement of the correlation between Sorrow and Tenderness from .87 to .81, the matrix is positive definite.

Alternatively, using `cor.smooth`, the matrix can be made positive definite as well, although cor.smooth makes more (but smaller) changes.

### Source

(retrieved from the web at http://www.biodiversitylibrary.org/item/95822#790) Following a suggestion by Jan DeLeeuw.

### References

Burt, C.General and Specific Factors underlying the Primary Emotions. Reports of the British Association for the Advancement of Science, 85th meeting, held in Manchester, September 7-11, 1915. London, John Murray, 1916, p. 694-696 (retrieved from the web at http://www.biodiversitylibrary.org/item/95822#790)

### See Also

`Harman.Burt` in the `Harman` dataset and `cor.smooth`

### Examples

    data(burt)
    eigen(burt)$values  #one is negative!
    burt.new <- burt
    burt.new[2,3] <- burt.new[3,2] <- .81
    eigen(burt.new)$values  #all are positive
    bs <- cor.smooth(burt)
    round(burt.new - bs,3)

[Package psych version 1.7.3.21 Index]