You are here:

Item Selection and Hypothesis Testing for the Adaptive Measurement of Change

, ,

Applied Psychological Measurement Volume 34, Number 4, ISSN 0146-6216


Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC framework. This study introduced a new item selection criterion and two new test statistics for detecting change with AMC that were specifically designed for the paradigm of hypothesis testing. In two simulation sets, the new methods for detecting significant change improved on existing procedures by demonstrating better adherence to Type I error rates and substantially better power for detecting relatively small change. (Contains 3 tables and 4 figures.)


Finkelman, M.D., Weiss, D.J. & Kim-Kang, G. (2010). Item Selection and Hypothesis Testing for the Adaptive Measurement of Change. Applied Psychological Measurement, 34(4), 238-254. Retrieved March 23, 2023 from .

This record was imported from ERIC on April 19, 2013. [Original Record]

ERIC is sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.

Copyright for this record is held by the content creator. For more details see ERIC's copyright policy.