Contributions to Mokken's nonparametric item response theory

In this study, the item response models proposed by Mokken (1971) are discussed, and further developed. In these item response models the relation between observable response behavior on an item and latent characteristics of persons and items is described by means of an item characteristic function. Since these functions are not defined parametrically in Mokken's approach, the item response models are called nonparametric. The models proposed by Mokken can be used to scale persons and items on a single dimension. This dimension represents the quantitative measurement scale of a psychological or some other attribute. By measuring persons by means of tests or questionnaires which comply with an item response model, assertions about behavior are psychometrically well founded. ... Zie: Summary

Part II: On the use, the misuse, and the very limited usefulness of Cronbach’s Alpha:Discussing lower bounds and correlated errors

Prior to discussing and challenging two criticisms on coefficient α, the well-known lower bound to test-score reliability, we discuss classical test theory and the theory of coefficient α. The first criticism expressed in the psychometrics literature is that coefficient α is only useful when the model of essential τ-equivalence is consistent with the item-score data. Because this model is highly restrictive, coefficient α is smaller than test-score reliability and one should not use it. We argue that lower bounds are useful when they assess product quality features, such as a test-score’s reliability. The second criticism expressed is that coefficient α incorrectly ignores correlated errors. If correlated errors would enter the computation of coefficient α, theoretical values of coefficient α could be greater than the test-score reliability. Because quality measures that are systematically too high are undesirable, critics dismiss coefficient α. We argue that introducing correlated errors is inconsistent with the derivation of the lower bound theorem and that the properties of coefficient α remain intact when data contain correlated errors

Rejoinder:The future of reliability

In this rejoinder, we examine some of the issues Peter Bentler, Eunseong Cho. and Jules Ellis raise. We suggest a methodological solid way to construct a test indicating that the importance of the particular reliability method used is minor, and we discuss future topics in reliability research

Advances in nonparametric item response theory for scale construction in quality-of-life research

We introduce the special section on nonparametric item response theory (IRT) in Quality of Life Research. Starting from the well-known Rasch model, we provide a brief overview of nonparametric IRT models and discuss the assumptions, the properties, and the investigation of goodness of fit. We provide references to more detailed texts to help readers getting acquainted with nonparametric IRT models. In addition, we show how the rather diverse papers in the special section fit into the nonparametric IRT framework. Finally, we illustrate the application of nonparametric IRT models using data from a questionnaire measuring activity limitations in walking. The real-data example shows the quality of the scale and its constituent items with respect to dimensionality, local independence, monotonicity, and invariant item ordering

Supervised dimensionality reduction for multiple imputation by chained equations

Multivariate imputation by chained equations (MICE) is one of the most popular approaches to address missing values in a data set. This approach requires specifying a univariate imputation model for every variable under imputation. The specification of which predictors should be included in these univariate imputation models can be a daunting task. Principal component analysis (PCA) can simplify this process by replacing all of the potential imputation model predictors with a few components summarizing their variance. In this article, we extend the use of PCA with MICE to include a supervised aspect whereby information from the variables under imputation is incorporated into the principal component estimation. We conducted an extensive simulation study to assess the statistical properties of MICE with different versions of supervised dimensionality reduction and we compared them with the use of classical unsupervised PCA as a simpler dimensionality reduction technique

Reliability estimation for single dichotomous items based on Mokken's IRT model

Item reliability is of special interest for Mokken’s nonparametric item response theory, and is useful for the evaluation of item quality in nonparametric test construction research. It is also of interest for nonparametric person-fit analysis. Three methods for the estimation of the reliability of single dichotomous items are discussed. All methods are based on the assumptions of nondecreasing and nonintersecting item response functions. Based on analytical and monte carlo studies, it is concluded that one method is superior to the other two, because it has a smaller bias and a smaller sampling variance. This method also demonstrated some robustness under violation of the condition of nonintersecting item response functions. Index terms: item reliability, item response theory, Mokken model, nonparametric item response models, test construction

Measuring cyber secure behavior of elementary and high school students in the Netherlands

School systems may pay attention to the fact that individuals and companies using smart devices are increasingly at risk of becoming victims of cybercrime. The literature on how effective students in developed countries such as the Netherlands are taught about cyber security skills during their school career is scarce. Although curriculum materials are available, scaling up computer science education is behind. Therefore, this study explores to what extent Dutch students develop cyber secure behavior at elementary and high school. A questionnaire was used for self-assessment of cyber security behavior. After the questionnaire was completed, two group interviews were conducted to improve the interpretation of the questionnaire results. The study findings revealed that the Dutch school curriculum hardly pays attention to this topic and that students acquire their online behavior mainly through experience, instructions on the internet, through parents, and through siblings. In addition, many students developed more reckless behavior over time. We recommend that cyber security education should start at elementary school as soon as children begin to use online equipment. A subject that deserves special attention is recognizing phishing emails and phishing websites. The learners should be convinced that risky behavior on the internet may turn against them and against the organization to which they belong