and the factor on which they are loaded. Generally, if an item displays a loading of 0.4 or above on a specific factor, then it is classed as loading on that factor. However, occasionally it is necessary to be more stringent and only accept a loading of 0.5 or greater. This is normally done when there are a large number of ambiguous items which load by 0.4 or above on both factors thus making them difficult to classify. Results - Time TwoFour items were removed during the reliability analysis meaning that only 16 items were inputted into the factor analysis process (see App 3, Table 2)Table 2 - Reasons for item removal at time 2ItemReason3The government should give in to the blockadesIncreases Alpha6The government should not give in to bully-boy tacticsMean * 3.58Fuel tax cuts are essential for businesses to surviveMean * 2.514The blockades have achieved good resultsMean * 3.5As can be seen from the table outlining the reasons why four items were removed from the scale before the final analysis and subsequent factor analysis, three of the items were removed because their means fell outside the required range (items 6, 8 and 14) and item 3 was removed because it increased the alpha if deleted. Final analysis of our scale revealed that the mean correlation between items was moderate to high (r = 0.67). This statistic indicates that all scale items appear to be measuring the same construct. Also, the overall item mean across all items is 3.1 which is around the figure expected on a response set containing five levels of agreement. Cronbachs Alpha for the scale indicated very high internal consistency ( = 0.97).A Pearsons correlation was carried out on the data from time one and time two and indicated a high level of test-retest reliability (r = 0.92, N = 46, P*0.001). This means the responses remained reasonably constant over the time interval between the two test dates. Further, the criterion related validity was assessed using an indep...
