Entries by Nathan Thompson, PhD

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Monte Carlo simulation in adaptive testing

Simulation studies are an essential step in the development of a computerized adaptive test (CAT) that is defensible and meets the needs of your organization or other stakeholders. There are three types of simulations: Monte Carlo, Real Data (post hoc), and Hybrid. Monte Carlo simulation is the most general-purpose approach, and the one most often […]

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What is decision consistency?

If you are involved with certification testing and are accredited by the National Commission of Certifying Agencies (NCCA), you have come across the term decision consistency.  NCCA requires you to submit a report of 11 important statistics each year, each for all active test forms.  These 11 provide a high level summary of the psychometric […]

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What is the Sympson-Hetter Item Exposure Control?

Sympson-Hetter is a method of item exposure control within the algorithm of Computerized adaptive testing (CAT).  It prevents the algorithm from over-using the best items in the pool. CAT is a powerful paradigm for delivering tests that are smarter, faster, and fairer than the traditional linear approach.  However, CAT is not without its challenges.  One is […]

What is the Standard Error of the Mean?

The standard error of the mean is one of the three main standard errors in psychometrics and psychology.  Its purpose is to help conceptualize the error in estimating the mean of some population based on a sample.  The SEM is a well-known concept from the general field of statistics, used in an untold number of […]