R Dataset / Package psych / burt
On this Picostat.com statistics page, you will find information about the burt data set which pertains to 11 emotional variables from Burt (1915). The burt data set is found in the psych R package. Try to load the burt data set in R by issuing the following command at the console data("burt"). This may load the data into a variable called burt. If R says the burt data set is not found, you can try installing the package by issuing this command install.packages("psych") and then attempt to reload the data with library("psych") followed by data("burt"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing burt at the command-line which should display the entire dataset.
If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the burt R data set. The size of this file is about 746 bytes.
11 emotional variables from Burt (1915)
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.
A correlation matrix based upon 172 "normal school age children aged 9-12".
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
(retrieved from the web at http://www.biodiversitylibrary.org/item/95822#790) Following a suggestion by Jan DeLeeuw.
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)
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)
Dataset imported from https://www.r-project.org.
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