elementCor: Calculate the correlations between elements.

Description

Note that simple element correlations as a measure of similarity are flawed as they are not invariant to construct reflection (Mackay, 1992; Bell, 2010). A correlation index invariant to construct reflection is Cohen's rc measure (1969), which can be calculated using the argument rc=TRUE which is the default option.

Usage

elementCor(x, rc = TRUE, method = "pearson", trim = 20, index = TRUE)

Value

matrix of element correlations

Arguments

x: repgrid object.
rc: Use Cohen's rc which is invariant to construct reflection (see description above). It is used as the default.
method: A character string indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall" or "spearman", can be abbreviated. The default is "pearson".
trim: The number of characters a construct is trimmed to (default is 20). If NA no trimming occurs. Trimming simply saves space when displaying correlation of constructs with long names.
index: Whether to print the number of the construct.

References

Bell, R. C. (2010). A note on aligning constructs. Personal Construct Theory & Practice, (7), 42-48.

Cohen, J. (1969). rc: A profile similarity coefficient invariant over variable reflection. Psychological Bulletin, 71(4), 281-284.

Mackay, N. (1992). Identification, Reflection, and Correlation: Problems In The Bases Of Repertory Grid Measures. International Journal of Personal Construct Psychology, 5(1), 57-75.

Examples

Run this code

elementCor(mackay1992) # Cohen's rc
elementCor(mackay1992, rc = FALSE) # PM correlation
elementCor(mackay1992, rc = FALSE, method = "spearman") # Spearman correlation

# format output
elementCor(mackay1992, trim = 6)
elementCor(mackay1992, index = FALSE, trim = 6)

# save as object for further processing
r <- elementCor(mackay1992)
r

# change output of object
print(r, digits = 5)
print(r, col.index = FALSE)
print(r, upper = FALSE)

# accessing elements of the correlation matrix
r[1, 3]