On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large‐sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process.     

An R package to compute commonality coefficients in the multiple regression case: An introduction to the package and a practical example

Multiple regression is a widely used technique for data analysis in social and behavioral research. The complexity of interpreting such results increases when correlated predictor variables are involved. Commonality analysis provides a method of determining the variance accounted for by respective predictor variables and is especially useful in the presence of correlated predictors. However, computing commonality coefficients is laborious. To make commonality analysis accessible to more researchers, a program was developed to automate the calculation of unique and common elements in commonality analysis, using the statistical package R. The program is described, and a heuristic example using data from the Holzinger and Swineford (1939) study, readily available in the MBESS R package, is presented.     

Counselling and health: An introduction

The special issue on 'Counselling and Health' is introduced, and the context in which counsellors are concerned with both well-being and ill-health is explored.     

Addictions and the family: An introduction

The editors of this special issue would like to express their appreciation to William C. Nichols, editor ofContemporary Family Therapy, for his support and encouragement in putting together this issue. We would also like to acknowledge and thank H. Allan Dye, Joan Jurich, Kevin R. Kelly, Richard M. Loughead, Nancy Shook, and Paul H. Wright for their patience, assistance, and editorial reviews.