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The steps to conduct a reliability analysis using spss, specifically calculating cronbach's alpha for a given set of items. The analysis involves moving items into the 'items' window, ensuring 'alpha' is selected in the 'model' window, and clicking the 'statistics' button with 'scale' and 'scale if item deleted' checked. The document also discusses interpreting the results, including corrected item-total correlation and alpha if item deleted.
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Using SPSS Reliabilities
Analyze ‡ Scale ‡ Reliabilities
Move the desired items into the “Items” window.
Be sure “Alpha” is showing in the Model window
Click the “Statistics” button
Be sure “Scale” and “Scale if item deleted” buttons are checked.
****** Method 1 (space saver) will be used for this analysis ****** _
N of Statistics for Mean Variance Std Dev Variables SCALE 24.6419 24.1512 4.9144 8
Item-total Statistics
Scale Scale Corrected Mean Variance Item- Alpha if Item if Item Total if Item Deleted Deleted Correlation Deleted
Reliability Coefficients
N of Cases = 1142.0 N of Items = 8
Alpha =.
Alpha shows the Cronbach’s a value for the item set – values > .70 are usually considered good.
First, look at the Corrected Item-Total Correlation. This is the correlation between each item and a scale score that excludes that item (uses all the other items, but not that one). Items with negative item-total correlations probably aren’t good items. But don’t discard more than 1-2 at a time.
Next, carefully evaluate the “Alpha if Item Deleted” for each item. You are looking for items that, if deleted, will lead to a “substantial” increase in the scale a. Don’t get carried away (you can lose a lot of items quickly) and don’t discard more than an item or at most two at a time.
