Using likert-type scale items, professor weston developed an index to assess job morale. weston administered the index to 2,000 workers and found that 1/3 responses were missing on each of the items. to deal with the missing data, professor weston could a. exclude the cases that contained the missing data from the analysis. b. assign the middle value to cases with missing data. c. analyze the case that had missing data to interpret their meaning. d. assign values at random. e. all of the above.

e. All of the above.

Explanation:

"The effects of using two methods (item mean and person mean) for replacing missing data in Likert scales were studied. The results showed that both methods were good representations of the original data when both the number of respondents with missing data and the number of items missing were 20% or less. As the numbers of missing items and of respondents with missing data increased for the person mean substitution method, a spurious increase in the inter-item correlations (and, therefore, reliability) for the scale was produced. The item mean substitution reduced the reliability estimates of the scale. These results suggest caution in the use of the person mean substitution method as the numbers of missing items and respondents increase."

Reference: Downey, Ronald, and Craig King. “Missing Data in Likert Ratings: A Comparison of Replacement Methods.” Taylor & Francis, 2010

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