Biomedical subjects

H A Kiers

Publications and source records attributed to H A Kiers.

3 recordsLinked to original sources

PubMed2001

Construct validity of concepts of attention in healthy controls and patients with CHI.

The present study aimed to examine the construct validity of three aspects of attention, namely focused, divided, and supervisory control of attention. Factor-analytic techniques were applied to scores of healthy subjects on a series of neuropsychological tests tapping these aspects of attention. The two components found did not match the hypothesized aspects and were labeled as Memory-driven Action and Stimulus-driven Reaction. The second question was whether the same components could be found in a group of patients with CHI. The pattern of attentional functions found in healthy subjects had changed qualitatively in patients with CHI. A possible explanation for this result in terms of a shift from automatic to controlled processing is discussed.

Adolescent↗

PubMed2001

Three-way component analysis: principles and illustrative application.

Three-way component analysis techniques are designed for descriptive analysis of 3-way data, for example, when data are collected on individuals, in different settings, and on different measures. Such techniques summarize all information in a 3-way data set by summarizing, for each way of the 3-way data set, the associated entities through a few components and describing the relations between these components. In this article, 3-mode principal components analysis is described at an elementary level. Guidance is given concerning the choices to be made in each step of the process of analyzing 3-way data by this technique. The complete process is illustrated with a detailed description of the analysis of an empirical 3-way data set.

Analysis of Variance↗

PubMed2000

Three-mode principal components analysis: choosing the numbers of components and sensitivity to local optima.

A method that indicates the numbers of components to use in fitting the three-mode principal components analysis (3MPCA) model is proposed. This method, called DIFFIT, aims to find an optimal balance between the fit of solutions for the 3MPCA model and the numbers of components. The achievement of DIFFIT is compared with that of two other methods, both based on two-way PCAs, by means of a simulation study. It was found that DIFFIT performed considerably better than the other methods in indicating the numbers of components. The 3MPCA model can be estimated by the TUCKALS3 algorithm, which is an alternating least squares algorithm. In a study of how sensitive TUCKALS3 is at hitting local optima, it was found that, if the numbers of components are specified correctly, TUCKALS3 never hits a local optimum. The occurrence of local optima increased as the difference between the numbers of underlying components and the numbers of components as estimated by TUCKALS3 increased. Rationally initiated TUCKALS3 runs hit local optima less often than randomly initiated runs.

Algorithms↗