Biomedical subjects

Kit-Tai Hau

Publications and source records attributed to Kit-Tai Hau.

4 recordsLinked to original sources

PubMed2005

Computerized adaptive testing: a mixture item selection approach for constrained situations.

In computerized adaptive testing (CAT), traditionally the most discriminating items are selected to provide the maximum information so as to attain the highest efficiency in trait (theta) estimation. The maximum information (MI) approach typically results in unbalanced item exposure and hence high item-overlap rates across examinees. Recently, Yi and Chang (2003) proposed the multiple stratification (MS) method to remedy the shortcomings of MI. In MS, items are first sorted according to content, then difficulty and finally discrimination parameters. As discriminating items are used strategically, MS offers a better utilization of the entire item pool. However, for testing with imposed non-statistical constraints, this new stratification approach may not maintain its high efficiency. Through a series of simulation studies, this research explored the possible benefits of a mixture item selection approach (MS-MI), integrating the MS and MI approaches, in testing with non-statistical constraints. In all simulation conditions, MS consistently outperformed the other two competing approaches in item pool utilization, while the MS-MI and the MI approaches yielded higher measurement efficiency and offered better conformity to the constraints. Furthermore, the MS-MI approach was shown to perform better than MI on all evaluation criteria when control of item exposure was imposed.

Computer-Aided Design↗

PubMed2004

Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction.

Interactions between (multiple indicator) latent variables are rarely used because of implementation complexity and competing strategies. Based on 4 simulation studies, the traditional constrained approach performed more poorly than did 3 new approaches--unconstrained, generalized appended product indicator, and quasi-maximum-likelihood (QML). The authors' new unconstrained approach was easiest to apply. All 4 approaches were relatively unbiased for normally distributed indicators, but the constrained and QML approaches were more biased for nonnormal data; the size and direction of the bias varied with the distribution but not with the sample size. QML had more power, but this advantage was qualified by consistently higher Type I error rates. The authors also compared general strategies for defining product indicators to represent the latent interaction factor.

Analysis of Variance↗

PubMed2004

The use of item parcels in structural equation modelling: non-normal data and small sample sizes.

Maximum likelihood estimation in confirmatory factor analysis requires large sample sizes, normally distributed item responses, and reliable indicators of each latent construct, but these ideals are rarely met. We examine alternative strategies for dealing with non-normal data, particularly when the sample size is small. In two simulation studies, we systematically varied: the degree of non-normality; the sample size from 50 to 1000; the way of indicator formation, comparing items versus parcels; the parcelling strategy, evaluating uniformly positively skews and kurtosis parcels versus those with counterbalancing skews and kurtosis; and the estimation procedure, contrasting maximum likelihood and asymptotically distribution-free methods. We evaluated the convergence behaviour of solutions, as well as the systematic bias and variability of parameter estimates, and goodness of fit.

Factor Analysis, Statistical↗

PubMed2003

Big-fish-little-pond effect on academic self-concept. A cross-cultural (26-country) test of the negative effects of academically selective schools.

Academically selective schools are intended to affect academic self-concept positively, but theoretical and empirical research demonstrates that the effects are negative. The big-fish-little-pond effect (BFLPE), an application of social comparison theory to educational settings, posits that a student will have a lower academic self-concept in an academically selective school than in a nonselective school. This study, the largest cross-cultural study of the BFLPE ever undertaken, tested theoretical predictions for nationally representative samples of approximately 4,000 15-year-olds from each of 26 countries (N = 103,558) who completed the same self-concept instrument and achievement tests. Consistent with the BFLPE, the effects of school-average achievement were negative in all 26 countries (M beta = -.20, SD = .08), demonstrating the BFLPE's cross-cultural generalizability.

Adolescent↗