Abstract
When conducting an analysis of test data or survey data using Rasch techniques, missing data often is not a big problem – a student skipping an item on a test can be measured using the items they attempt. In fact, when linking test or survey forms, the issue can be thought of, in part, as a missing data issue. In this chapter we discuss why missing data often will not impact the measurement of a respondent. However, we also discuss the issue of how to view missing data. For example, should skipped items be items counted as “wrong” but items “not reached” be counted as “missing”? In this chapter, we consider several missing data issues and we explain how Winsteps can allow one to experiment with the coding of missing data with the goal of conducting accurate measures of respondents. The chapter finishes up with a student dialogue, Keywords and Phrases, Quick Tips, Data Files, References, and Additional Readings. As in almost all chapters, sample analyses are used to reinforce the chapter topic.
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