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The mechanical properties of sclera play an important role in ocular functions, protection, and disease. Modulating the sclera's properties by exogenous crosslinking offers a way to expand the tissue's range of properties for study of the possible influences on the eye's behavior and diseases such as glaucoma and myopia. The focus of this work was to evaluate the effects of genipin crosslinking targeting the porcine perilimbal sclera (PLS) since the stiffness of this tissue was previously found in a number of studies to influence the eye's intraocular pressure (IOP). The work includes experiments on tensile test specimens and whole globes. The specimen tests showed decreased strain-rate dependence and increased relaxation stress due to the cross-linker. Whole globe perfusion experiments demonstrated that eyes treated with genipin in the perilimbal region had increased IOPs compared to the control globes. Migration of the cross-linker from the target tissue to other tissues is a confounding factor in whole globe, biomechanical measurements, with crosslinking. A novel quantitative genipin assay of the trabecular meshwork (TM) was developed to exclude globes where the TM was inadvertently crosslinked. The perfusion study, therefore, suggests that elevated stiffness of the PLS can significantly increase IOP apart from effects of the TM in the porcine eye. These results demonstrate the importance of PLS biomechanics in aqueous outflow regulation and support additional investigations into the distal outflow pathways as a key source of outflow resistance. [ABSTRACT FROM AUTHOR]

The Center for Epidemiologic Studies-Depression (CES-D) scale is a well-known self-report instrument that is used to measure depressive symptomatology. Respondents who take the full-length version of the CES-D are administered a total of 20 items. This article investigates the use of curtailment and stochastic curtailment (SC), two sequential analysis methods that have recently been proposed for health questionnaires, to reduce the respondent burden associated with taking the CES-D. A post hoc simulation based on 1,392 adolescents' responses to the CES-D was used to compare these methods with a previously proposed computerized adaptive testing (CAT) approach. Curtailment lowered average test lengths by as much as 22% while always matching the classification decision of the full-length CES-D. SC and CAT achieved further reductions in average test length, with SC's classifications exhibiting more concordance with the full-length CES-D than do CAT's. Advantages and disadvantages of each method are discussed. (Contains 5 tables and 2 figures.)

Automated test assembly (ATA) has been an area of prolific psychometric research. Although ATA methodology is well developed for unidimensional models, its application alongside cognitive diagnosis models (CDMs) is a burgeoning topic. Two suggested procedures for combining ATA and CDMs are to maximize the cognitive diagnostic index and to use a genetic algorithm. Each of these procedures has a disadvantage: The cognitive diagnostic index cannot control attribute-level information and the genetic algorithm is computationally intensive. The goal of this article is to solve both problems by using binary programming, together with the item discrimination indexes of Henson et al., for performing ATA with CDMs. The three procedures are compared in simulation. Advantages and disadvantages of each are discussed. (Contains 1 note, 4 tables, and 1 figure.)

The recent study of Oshima, Raju, and Nanda proposes the item parameter replication (IPR) method for assessing statistical significance of the noncompensatory differential item functioning (NCDIF) index within the differential functioning of items and tests (DFIT) framework. Previous Monte Carlo simulations have found that the appropriate cutoff values for determining statistical significance of NCDIF depend on sample size and the item response theory (IRT) model used for the analysis. The IPR method simplifies the process of identifying cutoff values that are tailored to a particular research setting. This approach has been shown to be effective for detecting differential item functioning (DIF) in dichotomous items. The current article extends the IPR method to the polytomous case. (Contains 2 tables, 1 figure and 2 notes.)

Much recent psychometric literature has focused on cognitive diagnosis models (CDMs), a promising class of instruments used to measure the strengths and weaknesses of examinees. This article introduces a genetic algorithm to perform automated test assembly alongside CDMs. The algorithm is flexible in that it can be applied whether the goal is to minimize the average number of classification errors, minimize the maximum error rate across all attributes being measured, hit a target set of error rates, or optimize any other prescribed objective function. Under multiple simulation conditions, the algorithm compared favorably with a standard method of automated test assembly, successfully finding solutions that were appropriate for each stated goal.