Nomothetic Item Selection Rules for Tests of Psychological Interventions

1997 ◽  
Vol 7 (4) ◽  
pp. 419-427 ◽  
Author(s):  
Scott Meier
2010 ◽  
Vol 34 (6) ◽  
pp. 438-452 ◽  
Author(s):  
Juan Ramón Barrada ◽  
Julio Olea ◽  
Vicente Ponsoda ◽  
Francisco José Abad

2020 ◽  
Vol 44 (7-8) ◽  
pp. 531-547
Author(s):  
Johan Braeken ◽  
Muirne C. S. Paap

Fixed-precision between-item multidimensional computerized adaptive tests (MCATs) are becoming increasingly popular. The current generation of item-selection rules used in these types of MCATs typically optimize a single-valued objective criterion for multivariate precision (e.g., Fisher information volume). In contrast, when all dimensions are of interest, the stopping rule is typically defined in terms of a required fixed marginal precision per dimension. This asymmetry between multivariate precision for selection and marginal precision for stopping, which is not present in unidimensional computerized adaptive tests, has received little attention thus far. In this article, we will discuss this selection-stopping asymmetry and its consequences, and introduce and evaluate three alternative item-selection approaches. These alternatives are computationally inexpensive, easy to communicate and implement, and result in effective fixed-marginal-precision MCATs that are shorter in test length than with the current generation of item-selection approaches.


2017 ◽  
Vol 33 (6) ◽  
pp. 409-421 ◽  
Author(s):  
Anne B. Janssen ◽  
Martin Schultze ◽  
Adrian Grötsch

Abstract. Employees’ innovative work is a facet of proactive work behavior that is of increasing interest to industrial and organizational psychologists. As proactive personality and supervisor support are key predictors of innovative work behavior, reliable, and valid employee ratings of these two constructs are crucial for organizations’ planning of personnel development measures. However, the time for assessments is often limited. The present study therefore aimed at constructing reliable short scales of two measures of proactive personality and supervisor support. For this purpose, we compared an innovative approach of item selection, namely Ant Colony Optimization (ACO; Leite, Huang, & Marcoulides, 2008 ) and classical item selection procedures. For proactive personality, the two item selection approaches provided similar results. Both five-item short forms showed a satisfactory reliability and a small, however negligible loss of criterion validity. For a two-dimensional supervisor support scale, ACO found a reliable and valid short form. Psychometric properties of the short version were in accordance with those of the parent form. A manual supervisor support short form revealed a rather poor model fit and a serious loss of validity. We discuss benefits and shortcomings of ACO compared to classical item selection approaches and recommendations for the application of ACO.


Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 177-188 ◽  
Author(s):  
Martin Schultze ◽  
Michael Eid

Abstract. In the construction of scales intended for the use in cross-cultural studies, the selection of items needs to be guided not only by traditional criteria of item quality, but has to take information about the measurement invariance of the scale into account. We present an approach to automated item selection which depicts the process as a combinatorial optimization problem and aims at finding a scale which fulfils predefined target criteria – such as measurement invariance across cultures. The search for an optimal solution is performed using an adaptation of the [Formula: see text] Ant System algorithm. The approach is illustrated using an application to item selection for a personality scale assuming measurement invariance across multiple countries.


Sign in / Sign up

Export Citation Format

Share Document