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supervisor LMX score of each participant from their respective mean subordinate
LMX score. This variable was called LMX difference. Greater LMX agreement is
found, when the value of LMX difference is near to zero. Bivariate correlations
(Pearson’s correlation analysis) were employed to analyse the relationship among
variables.
Table 25: Correlations Analysis
LMX
Difference AOC TI LMX SLMX
LMX Difference 1
AOC -.402 ** 1
TI .165 ** -.360 ** 1
LMX -.629 ** .652 ** -.286 ** 1
Supervisor LMX .671 ** .111 -.063 .154 ** 1
Note: ** Correlation is significant at the 0.01 level (2-tailed), n = 315
Table 25 shows a moderate negative relationship (-.402) between the scores of LMX
difference and organisational commitment (AOC) among the 315 respondents. A
moderate correlation lies between 0.30 and 0.49 (Hopkins, 2006). The association (-
.402) was significant at less than 0.001 level (two-tailed). A two-tailed test is a
statistical test in which the correlation values are either greater than or less than a
certain value (Bartholomew et al., 2008). Further, the coefficient of determination, R
Square (R 2 ) was .161 which implies that LMX difference accounts for 16.1 % of the
variance of the subordinate’s organisational commitment.
It is evident from these results that the higher the difference between the mean scores
of supervisor and subordinate LMX, the lower the subordinate’s affective
organisational score. In other words, the greater the agreement between the mean LMX
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