I__. - International Military Testing Association

with) strong platoon performance at the JRTC or NTC. Among all
the predictor constructs, JRTC/NTC motivation and job motivation
were the strongest correlates with the OC criterion ratings, .65
and .63 respectively. Their correlations were also reduced when
job satisfaction was controlled, to .34 and .27.
Regardless of the large common variance among the predictor
construct scales, a critical concern was whether the common
variance among the predictor scales was due in part to the level
of task and mission training. If this were the case, then the
correlations with the criteria ratings could be simply an
instance of high or low training at pre-rotation resulting in
high or low performance at JRTC or NTC. To examine this, partial
correlations were again computed controlling for the squad
members' pre-rotation estimates of their platoon's level of task
and mission training (measured using the same response scale as
the criterion raters). The results are given in Table 3.
Table 3. Partial Correlations Between Cohesion and Platoon
Average Mission Performance at JRTC or NTC by Rater of
Performance, Controlling for Pre-rotation Training Level
Cohesion Scale
SMHB
Performance Raters
oc co PLT
. 49** .32* .22
LHB .49* .16 .30*
VB �
42* .20 .lEj
PRIDE . 55** .27* .I7
AI . 39* .21 .16 --
* = pc.05; ** = PC.01 N= 20 39 55
As Table 3 shows, the partial correlations (with perceived
training level controlled) are not much different from the direct
correlations given in Table 1.a. Also, there was no or little
change from the direct correlations for the other major predictor
constructs, with training controlled. A fair interpretation of
Table 3 would be that cohesion adds significantly to the mission
performance of platoons at training centers such as the JRTC and
the NTC beyond that portion of performance due to level of
training. In other words, cohesion and other job related and
organizational constructs provide a separate, important
contribution to performance. Speculating from the data in this
research, one can estimate that separate contribution to be in
the range of 10 - 40% of the performance variance. Obviously,
further research remains to be done in sorting out the nature and
inter-relationships of the predictor constructs and in
determining the constructs' relationship with performance across
the range of construct values (e.g., low, medium, and high levels
of the constructs).