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B W Junker

Publications and source records attributed to B W Junker.

4 recordsLinked to original sources

A survey of theory and methods of invariant item ordering.

In many testing situations, ordering the items by difficulty is helpful in analysing the testing data; examples include intelligence testing, analysis of differential item functioning, person-fit analysis, and exploring hypotheses about the order in which cognitive operations are acquired by children. In each situation, interpretation and analysis are made easier if the items are ordered by difficulty in the same way for every individual taking the test, i.e. the item response functions do not cross. This is an invariant item ordering. In this paper we review a class of non-parametric unidimensional item response models in which the ordinal properties of items (and persons) can be studied, and survey both old and new methods for the investigation of invariant item ordering in empirical data sets. Our model formulation derives in particular from the work of Holland & Rosenbaum (1986), Junker (1993) and Mokken (1971). We survey methods based on the work of Mokken (1971), Rosenbaum (1987a, b), and Sijtsma & Meijer (1992), and we also discuss some new proposals for checking invariant item ordering. When violations are detected, these methods allow a rough assessment of where on the latent scale the item response functions cross. We also study similarities and differences between these various methods and provide guidelines for their use. Finally, the methods are illustrated with data from a developmental psychology experiment in which the ability to draw inferences about transitive relations is explored.

Child Development↗

A three-sample multiple-recapture approach to census population estimation with heterogeneous catchability.

"A central assumption in the standard capture-recapture approach to the estimation of the size of a closed population is the homogeneity of the 'capture' probabilities. In this article we develop an approach that allows for varying susceptibility to capture through individual parameters using a variant of the Rasch model from psychological measurement situations. Our approach requires an additional recapture. In the context of census undercount estimation, this requirement amounts to the use of a second independent sample or alternative data source to be matched with census and Post-Enumeration Survey (PES) data.... We illustrate [our] models and their estimation using data from a 1988 dress-rehearsal study for the 1990 census conducted by the U.S. Bureau of the Census, which explored the use of administrative data as a supplement to the PES. The article includes a discussion of extensions and related models."

Americas↗

Factor composition of the Suicide Intent Scale.

An exploratory analysis of the Suicide Intent Scale was performed on a sample of 98 psychiatric inpatients who had made suicide attempts. The factor analysis was performed using a method for polychotomous data, and resulted in a two-factor solution. The Lethal Intent factor contained items pertaining to the subjective level of lethal intent, while the Planning factor contained items largely related to objective planning for the attempt. Preliminary analysis of these factors suggest that the Suicide Intent Scale can be used to evaluate two separate aspects of suicidal behavior.

Adjustment Disorders↗

Exploratory statistical methods, with applications to psychiatric research.

This article introduces statistical methods for describing and summarizing the results of studies and introduces statistical principles that will guide the psychiatric researcher in the evaluation and interpretation of clinical research. We discuss relatively easy-to-use and informal methods for describing and comparing data. Our aim is to develop methods for investigating relationships among variables, to learn about the effect of one variable upon another. Once we have observed an apparent relationship between variables, an important question to be addressed is whether or not this observed relationship is causal in the sense that a change in one variable causes a changes in the other. We discuss and illustrate principles related to the evaluation of the nature of the association among variables. Throughout the article, principles and methods will be illustrated by examples and case studies based on data sets primarily from the psychiatric research literature.

Clinical Trials as Topic↗