Snijders developed a family of person fit indices that asymptotically follow the standard normal distribution, when the ability parameter is estimated. So far, lz*, U*, W*, ECI2z*, and ECI4z* from this family have been proposed in previous literature. One common property shared by lz*, U*, and W* (also ECI2z* and ECI4z* in some specific conditions) is that they employ symmetric weight functions and thus identify spurious scores on both easy and difficult items in the same manner. However, when the purpose is to detect only the spuriously high scores on difficult items, such as cheating, guessing, and having item preknowledge, using symmetric weight functions may jeopardize the detection rates of the target aberrant response patterns. By specifying two types of asymmetric weight functions, this study proposes SHa(λ)* (λ = 1/2 or 1) and SHb(β)* (β = 2 or 3) based on Snijders’s framework to specifically detect spuriously high scores on difficult items. Two simulation studies were carried out to investigate the Type I error rates and empirical power of SHa(λ)* and SHb(β)*, compared with lz*, U*, W*, ECI2z*, and ECI4z*. The empirical results demonstrated satisfactory performance of the proposed indices. Recommendations were also made on the choice of different person fit indices based on specific purposes.
Applied Psychological Measurement – SAGE
Published: Jul 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
All the latest content is available, no embargo periods.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud