An Iterative Scale Purification Procedure on lz for the Detection of Aberrant Responses

Many person-fit statistics have been proposed to detect aberrant response behaviors (e.g., cheating, guessing). Among them, lz is one of the most widely used indices. The computation of lz assumes the item and person parameters are known. In reality, they often have to be estimated from data. The better the estimation, the better lz will perform. When aberrant behaviors occur, the person and item parameter estimations are inaccurate, which in turn degrade the performance of lz. In this study, an iterative procedure was developed to attain more accurate person parameter estimates for improved performance of lz. A series of simulations were conducted to evaluate the iterative procedure under two conditions of item parameters, known and unknown, and three aberrant response styles of difficulty-sharing cheating, random-sharing cheating, and random guessing. The results demonstrated the superiority of the iterative procedure over the non-iterative one in maintaining control of Type-I error rates and improving the power of detecting aberrant responses. The proposed procedure was applied to a high-stake intelligence test.

Comparing the Performance of Eight Item Preknowledge Detection Statistics

Item preknowledge describes a situation in which a group of examinees (called aberrant examinees) have had access to some items (called compromised items) from an administered test prior to the exam. Item preknowledge negatively affects both the corresponding testing program and its users (e.g., universities, companies, government organizations) because scores for aberrant examinees are invalid. In general, item preknowledge is hard to detect due to multiple unknowns: unknown groups of aberrant examinees (at unknown test centers or schools) accessing unknown subsets of items prior to the exam. Recently, multiple statistical methods were developed to detect compromised items. However, the detected subset of items (called the suspicious subset) naturally has an uncertainty due to false positives and false negatives. The uncertainty increases when different groups of aberrant examinees had access to different subsets of items; thus, compromised items for one group are uncompromised for another group and vice versa. The impact of uncertainty on the performance of eight statistics (each relying on the suspicious subset) was studied. The measure of performance was based on the receiver operating characteristic curve. Computer simulations demonstrated how uncertainty combined with various independent variables (e.g., type of test, distribution of aberrant examinees) affected the performance of each statistic.

The cell-mediated immunity of Drosophila melanogaster: hemocyte lineages, immune compartments, microanatomy and regulation

In the animal kingdom, innate immunity is the first line of defense against invading pathogens. The dangers of microbial and parasitic attacks are countered by similar mechanisms, involving the prototypes of the cell-mediated immune responses, the phagocytosis and encapsulation. Work on Drosophila has played an important role in promoting an understanding of the basic mechanisms of phylogenetically conserved modules of innate immunity. The aim of this review is to survey the developments in the identification and functional definition of immune cell types and the immunological compartments of Drosophila melanogaster. We focus on the molecular and developmental aspects of the blood cell types and compartments, as well as the dynamics of blood cell development and the immune response. Further advances in the characterization of the innate immune mechanisms in Drosophila will provide basic clues to the understanding of the importance of the evolutionary conserved mechanisms of innate immune defenses in the animal kingdom.