Presenter:  Anli Lin
Presentation type:  Poster
Presentation date/time:  7/27  5:30-6:30
 
Equating Designs Comparison: Matched-Sample versus Common-Person Design
 
Anli Lin, Harcourt Assessment, Inc
Don Meagher, Harcourt Assessment,Inc
Christina Stellato, Harcourt Assessment,Inc
 
The purpose of this study was to develop an effective way to get equivalent groups for equating purposes using a matched-sample method, and to compare equating results obtained by using matched samples with equating results obtained by using a common-person design. The results of this study show that an equating parameter derived from the matched-sample method is very close to an equating parameter derived from a common-person design: the difference between the two designs is only about 0.1 scaled score unit (mean 400; standard deviation 25). In the paper, we consider the theoretical assumptions that support using the matched-sample method to determining equivalent groups and discuss the practical operations involved in using this method. Our findings suggest two major advantages to using the matched-sample method as compared to a common-person design. First, the data available to use with the matched-sample method comes from a large sample size, which makes the results more accurate and reliable than would be the case with a smaller sample size, which is often for common person design. The second advantage is that because we are able to use existing data with the matched-sample method, we do not need any extra design and operational efforts to collect common person data, which saves the time and money involved in conducting a research study in the field. For these reasons, we recommend using the matched-sample method whenever existing data is available, especially for renorming an existing test.