Biomedical subjects

David Thissen

Publications and source records attributed to David Thissen.

3 recordsLinked to original sources

PubMed2006

Using effect sizes for research reporting: examples using item response theory to analyze differential item functioning.

The psychological literature currently emphasizes reporting the "effect size" of research findings in addition to the outcome of any tests of significance. However, some confusion may result from the fact that there are three distinct uses of effect sizes in the psychological literature, namely, power analysis, research synthesis, and research reporting. The authors review these uses of effect sizes and develop a case study of the description of effect size for research reporting in the context of item response theory. For many parametric models, hypotheses are tested by comparing the values of directly interpretable parameters. The authors show that the size of the effect can be expressed by a presentation of the values of the parameter estimates derived from the fitted model. Studies that use item response theory to detect differential item functioning provide illustrations.

Humans↗

PubMed2006

Identification of differential item functioning using item response theory and the likelihood-based model comparison approach. Application to the Mini-Mental State Examination.

BACKGROUND: An important part of examining the adequacy of measures for use in ethnically diverse populations is the evaluation of differential item functioning (DIF) among subpopulations such as those administered the measure in different languages. A number of methods exist for this purpose. OBJECTIVE: The objective of this study was to introduce and demonstrate the identification of DIF using item response theory (IRT) and the likelihood-based model comparison approach. METHODS: Data come from a sample of community-residing elderly who were part of a dementia case registry. A total of 1578 participants were administered either an English (n = 913) or Spanish (n = 665) version of the 21-item Mini-Mental State Examination. IRT was used to identify language DIF in these items with the likelihood-based model comparison approach. RESULTS: : Fourteen of the 21 items exhibited significant DIF according to language of administration. However, because the direction of the identified DIF was not consistent for one language version over the other, the impact at the scale level was negligible. CONCLUSIONS: IRT and the likelihood-based model comparison approach comprise a powerful tool for DIF detection that can aid in the development, refinement, and evaluation of measures for use in ethnically diverse populations.

Aged↗

PubMed2006

Limited-information goodness-of-fit testing of item response theory models for sparse 2 tables.

Bartholomew and Leung proposed a limited-information goodness-of-fit test statistic (Y) for models fitted to sparse 2(P ) contingency tables. The null distribution of Y was approximated using a chi-squared distribution by matching moments. The moments were derived under the assumption that the model parameters were known in advance and it was conjectured that the approximation would also be appropriate when the parameters were to be estimated. Using maximum likelihood estimation of the two-parameter logistic item response theory model, we show that the effect of parameter estimation on the distribution of Y is too large to be ignored. Consequently, we derive the asymptotic moments of Y for maximum likelihood estimation. We show using a simulation study that when the null distribution of Y is approximated using moments that take into account the effect of estimation, Y becomes a very useful statistic to assess the overall goodness of fit of models fitted to sparse 2(P) tables.

Binomial Distribution↗