Construct Root-mean square correlation

Description
The Root mean square (RMS) is also known as 'quadratic mean' of the inter-construct correlations. 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).

R-Code
> constructRmsCor(fbb2003)

Root-mean-square correlation of constructs

RMS clever - not bright               0.66 disorganized - organized          0.58 listens - doesn't hear            0.61 no clear view - clear view of life 0.46 understands me - no understanding 0.53 ambitious - no ambition           0.30 respected - not respected         0.62 distant - warm                    0.25 rather aggressive - not aggressive 0.29

average of statistic 0.48 standard deviation of statistic 0.15

Constructs names can be trimmed and the number of digits to round to defined. > constructRmsCor(fbb2003, trim=10, digits=3)

Root-mean-square correlation of constructs

RMS cleve - not b 0.664 disor - organ 0.579 liste - doesn 0.611 no cl - clear 0.461 under - no un 0.532 ambit - no am 0.299 respe - not r 0.619 dista - warm 0.248 rathe - not a 0.292

average of statistic 0.478 standard deviation of statistic 0.151

If the results must not be seen during calculation the prtining to the console can be surpressed using output=0. Here the result are saved in the object r.

> r <- constructRmsCor(fbb2003, out=0) > r                                   RMS clever - not bright               0.66 disorganized - organized          0.58 listens - doesn't hear            0.61 no clear view - clear view of life 0.46 understands me - no understanding 0.53 ambitious - no ambition           0.30 respected - not respected         0.62 distant - warm                    0.25 rather aggressive - not aggressive 0.29

Literature

 * Fransella, F., Bell, R. C., & Bannister, D. (2003). A Manual for Repertory Grid Technique (2nd ed.). Chichester: John Wiley & Sons.