knitr::opts_chunk$set(collapse = TRUE, comment = "#") library(OpenRepGrid) options(width=120) settings(show.scale=FALSE, show.meta=FALSE)
The correlations between constructs are used in a lot of occasions, indices etc, and present a standard statistic. Several types of correlations can be requested via the function constructCor
.
Also, the Root mean square (RMS) correlation, also known as 'quadratic mean' of the inter-construct correlations, can be calculated using the function constructRmsCor
. The RMS serves as a simplification of the correlation table. It reflects the average relation of one construct with all other constructs. Note that as the correlations are squared during its calculation, the RMS is not affected by the sign of the correlation (cf. Fransella, Bell & Bannister, 2003, p. 86).
As suggested by Hinkle (1965) the relationships between constructs may take several different forms (reciprocal, hierarchical etc.). Several authors have suggested the use of asymmetric measures of association as an indicator for the type of relationship present (cf. Fransella et al., 2003). Currently only the software Gridstat (Bell, 2009) allows to calculate the asymmetric measure Somers’ D (Somers, 1962). The calculation of Somers' D in OpenRepGrid
is prompted via the function constructD
.
constructCor(mackay1992)
you can select between the different types of correlation by setting the argument method
to "pearson"
, "kendall"
or "spearman"
. To request a Spearman rank correlation type
constructCor(mackay1992, method="spearman")
To format the output several arguments are available. See ?print.constructCor
for more printing options.
r <- constructCor(mackay1992) print(r, digits=5, col.index=F)
To calulate the RMS correlation
constructRmsCor(fbb2003)
Somers' D is an asymmetric measure. As a default the columns are the dependent the rows the independent variables.
constructD(fbb2003)
To set the rows as dependent, type
constructD(fbb2003, dep="r")
The returned data is in all cases a matrix
or a data.frame
, so you can easily extract the data you need for further calculations.
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