1. One of the main issues concerns the scale’s internal consistency. This refers to the degree to which the items that make up the scale ‘hang together’ 2. One of the most commonly used indicators of internal consistency is Cronbach’s alpha coefficient. Ideally, the Cronbach’s alpha coefficient of a scale should be above 0.7 3. Cronbach alpha values are, however, quite sensive to the number of items in the scale. With short scales (eg scales with fewer than ten items, it is common to find quite low Cronbach values (eg 0.5). In this case, it may be more appropriate to report the mean inter-item correlaon for the items. 4. The reliability of a scale can vary depending on the sample with which it is used. It is therefore necessary to check that each of your scales is reliable with your parcular sample 5. If your scale contains some items that are negavely worded (common in psychological measures), these need to be ‘reversed’ before checking reliability. Interpreng the Output: Bahagian_B 1. Check the Inter-Item Correlaon Matrix for negave values. All values should be posive, indicang that the items are measuring the same underlying characterisc. The presence of negave values could indicate that some of the items have not been correctly reverse scored. Incorrect scoring would also show up in the Item-Total Stascs table with negave values for Corrected Item Total Correlaon values. These should be checked carefully if you obtain a lower than expected Cronbach alpha 2. Check the Cronbach’s alpha value shown in the Reliability Stascs table. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .837 .880 15 3. The Corrected Item Total Correlaon values shown in the Item Total Stascs table give you an indicaon of the degree to which each item correlaons with the total score. a. Low values (less than 0.3) here indicate that the item is measuring something different from the scale as a whole. b. If your scale’s overall Cronbach alpha is too low (eg less than 0.7) and you have checked for incorrectly scored items, you may need to consider removing items with low-item total correlaons 4. In the column headed Alpha if Item Deleted, the impact of removing each item from the scale is given. a. Compare these values with the final alpha obtained. b. If any of these values in this column are higher than the final alpha value, you may want to consider removing this item from the scale.