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We discuss reliability definitions from the perspectives of classical test theory, factor analysis, and generalizability theory. For each method, we discuss the rationale, the estimation of reliability, and the goodness of fit of the model that defines the reliability coefficient to the data. Similarities and differences in the three approaches are highlighted. Finally, we provide a computational example using generated data to illustrate the differences among the different reliability methods.

Inhibition of fatty acid amide hydrolase (FAAH) potentiates endocannabinoid activity and is hypothesized to have therapeutic potential for mood and anxiety disorders and pain. The clinical profile of JNJ‐42165279, an oral selective FAAH inhibitor, was assessed by investigating the pharmacokinetics, pharmacodynamics, safety, and binding to FAAH in the brain of healthy human volunteers. Concentrations of JNJ‐42165279 (plasma, cerebrospinal fluid (CSF), urine) and fatty acid amides (FAA; plasma, CSF), and FAAH activity in leukocytes was determined in a phase I multiple ascending dose study. A positron emission tomography study with the FAAH tracer [11C]MK3168 was conducted to determine brain FAAH occupancy after single and multiple doses of JNJ‐42165279. JNJ‐42165279 administration resulted in an increase in plasma and CSF FAA. Significant blocking of brain FAAH binding of [11C]MK3168 was observed after pretreatment with JNJ‐42165279. JNJ‐42165279 produces potent central and peripheral FAAH inhibition. Saturation of brain FAAH occupancy occurred with doses ≥10 mg of JNJ‐42165279. No safety concerns were identified.

Mucosal immunity is often required for protection against respiratory pathogens but the underlying cellular and molecular mechanisms of induction remain poorly understood. Here, systems vaccinology was used to identify immune signatures after pulmonary or subcutaneous immunization of mice with pertussis outer membrane vesicles. Pulmonary immunization led to improved protection, exclusively induced mucosal immunoglobulin A (IgA) and T helper type 17 (Th17) responses, and in addition evoked elevated systemic immunoglobulin G (IgG) antibody levels, IgG-producing plasma cells, memory B cells, and Th17 cells. These adaptive responses were preceded by unique local expression of genes of the innate immune response related to Th17 (e.g., Rorc) and IgA responses (e.g., Pigr) in addition to local and systemic secretion of Th1/Th17-promoting cytokines. This comprehensive systems approach identifies the effect of the administration route on the development of mucosal immunity, its importance in protection against Bordetella pertussis, and reveals potential molecular correlates of vaccine immunity to this reemerging pathogen.Mucosal Immunology advance online publication 20 September 2017; doi:10.1038/mi.2017.81.

Norm statistics allow for the interpretation of scores on psychological and educational tests, by relating the test score of an individual test taker to the test scores of individuals belonging to the same gender, age, or education groups, et cetera. Given the uncertainty due to sampling error, one would expect researchers to report standard errors for norm statistics. In practice, standard errors are seldom reported; they are either unavailable or derived under strong distributional assumptions that may not be realistic for test scores. We derived standard errors for four norm statistics (standard deviation, percentile ranks, stanine boundaries and Z-scores) under the mild assumption that the test scores are multinomially distributed. A simulation study showed that the standard errors were unbiased and that corresponding Wald-based confidence intervals had good coverage. Finally, we discuss the possibilities for applying the standard errors in practical test use in education and psychology. The procedure is provided via the R function check.norms, which is available in the mokken package.

The human gut is colonized with a myriad of microbes, with substantial interpersonal variation. This complex ecosystem is an integral part of the gastrointestinal tract and plays a major role in the maintenance of homeostasis. Its dysfunction has been correlated to a wide array of diseases, but the understanding of causal mechanisms is hampered by the limited amount of cultured microbes, poor understanding of phenotypes, and the limited knowledge about interspecies interactions. Genome-scale metabolic models (GEMs) have been used in many different fields, ranging from metabolic engineering to the prediction of interspecies interactions. We provide showcase examples for the application of GEMs for gut microbes and focus on (i) the prediction of minimal, synthetic, or defined media; (ii) the prediction of possible functions and phenotypes; and (iii) the prediction of interspecies interactions. All three applications are key in understanding the role of individual species in the gut ecosystem as well as the role of the microbiota as a whole. Using GEMs in the described fashions has led to designs of minimal growth media, an increased understanding of microbial phenotypes and their influence on the host immune system, and dietary interventions to improve human health. Ultimately, an increased understanding of the gut ecosystem will enable targeted interventions in gut microbial composition to restore homeostasis and appropriate host-microbe crosstalk.

The human gut is colonized with a myriad of microbes, with substantial interpersonal variation. This complex ecosystem is an integral part of the gastrointestinal tract and plays a major role in the maintenance of homeostasis. Its dysfunction has been correlated to a wide array of diseases, but the understanding of causal mechanisms is hampered by the limited amount of cultured microbes, poor understanding of phenotypes, and the limited knowledge about interspecies interactions. Genome-scale metabolic models (GEMs) have been used in many different fields, ranging from metabolic engineering to the prediction of interspecies interactions. We provide showcase examples for the application of GEMs for gut microbes and focus on (i) the prediction of minimal, synthetic, or defined media; (ii) the prediction of possible functions and phenotypes; and (iii) the prediction of interspecies interactions. All three applications are key in understanding the role of individual species in the gut ecosystem as well as the role of the microbiota as a whole. Using GEMs in the described fashions has led to designs of minimal growth media, an increased understanding of microbial phenotypes and their influence on the host immune system, and dietary interventions to improve human health. Ultimately, an increased understanding of the gut ecosystem will enable targeted interventions in gut microbial composition to restore homeostasis and appropriate host-microbe crosstalk.

Over the past decade, Mokken scale analysis (MSA) has rapidly grown in popularity among researchers from many different research areas. This tutorial provides researchers with a set of techniques and a procedure for their application, such that the construction of scales that have superior measurement properties is further optimized, taking full advantage of the properties of MSA. First, we define the conceptual context of MSA, discuss the two item response theory (IRT) models that constitute the basis of MSA, and discuss how these models differ from other IRT models. Second, we discuss dos and don'ts for MSA; the don'ts include misunderstandings we have frequently encountered with researchers in our three decades of experience with real-data MSA. Third, we discuss a methodology for MSA on real data that consist of a sample of persons who have provided scores on a set of items that, depending on the composition of the item set, constitute the basis for one or more scales, and we use the methodology to analyse an example real-data set.

When we call a person reliable, we mean that one can trust her to do what she promised to do. In other words, a reliable person shows behavior one expects. Technical devices typically are classified as reliable or unreliable. As cars grow older, technical malfunctioning becomes more likely, and they gradually become unreliable, meaning they no longer can be expected to take you from A to B without problems. Technical definitions of reliability also have entered the nonscientific arena. The Merriam-Webster dictionary defines reliability as “the extent to which an experiment, test, or measuring procedure yields the same results on repeated trials” (retrieved from http://www.merriam-webster.com/dictionary/reliability). This definition emphasizes repeatability of results when one collects new data under the same conditions as data were collected previously, and it comes close to what psychometric reliability is. The Oxford...

This proceedings volume compiles and expands on selected and peer reviewed presentations given at the 81st Annual Meeting of the Psychometric Society (IMPS), organized by the University of North Carolina at Greensboro, and held in Asheville, North Carolina, July 11th to 17th, 2016.IMPS is one of the largest international meetings focusing on quantitative measurement in psychology, education, and the social sciences, both in terms of participants and number of presentations. The meeting built on the Psychometric Society's mission to share quantitative methods relevant to psychology, addressing a diverse set of psychometric topics including item response theory, factor analysis, structural equation modeling, time series analysis, mediation analysis, cognitive diagnostic models, and multi-level models. Selected presenters were invited to revise and expand their contributions and to have them peer reviewed and published in this proceedings volume.Previous volumes to showcase work from the Psychometric Society's meetings are New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (Springer, 2013), Quantitative Psychology Research: The 78th Annual Meeting of the Psychometric Society (Springer, 2015), Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014 (Springer, 2015), and Quantitative Psychology Research: The 80th Annual Meeting of the Psychometric Society, Beijing, 2015 (Springer, 2016).

The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution and thus avoids judgment error. A computational study using large numbers of items shows that DLCRC also is faster than LCRC and fast enough for practical purposes. Speed and objectivity render DLCRC superior to LCRC. A decisive feature of DLCRC is that it aims at closely approximating the multivariate distribution of item scores, which might render the method suited when test data are multidimensional. A simulation study focusing on multidimensionality shows that DLCRC in general has little bias relative to the true reliability and is relatively accurate compared to LCRC and classical lower bound methods coefficients α and λ2 and the greatest lower bound.

We respond to three commentaries on our discussion article on different conceptions of test score reliability. First, we discuss the use of standard errors for reliability estimates. Second, we discuss the desirability not to confuse issues pertaining to the dimensionality of the test data (closely related to construct validity) and the degree to which measurement values are repeatable under the same circumstances (i.e., the reliability issue). Third, we discuss a new reliability estimation method that is almost unbiased irrespective of the dimensionality of the test data.

The sensitivity and the specificity of four outlier scores were studied for four different discordancy tests. The outlier scores were the Mahalanobis distance, a robust version of the Mahalanobis distance, and two measures tailored to discrete data, known as O+ and G+. The discordancy tests were Tukey’s fences (a.k.a. boxplot). Tukey’s fences with adjustment for skewness (adjusted boxplot), the generalized extreme studentized deviate (ESD), and the transformed ESD (ESD-T). Outlier scores O+ and G+ performed better than the Mahalanobis distance and its robust version. Discordancy tests ESD-T and adjusted boxplot were advocated for high specificity and ESD for high sensitivity.Keywords: discordancy test, Mahalanobis distance, outlier detection in questionnaire data, outlier score O+, outlier score G+, robust Mahalanobis distance

ObjectiveThe Hospital Anxiety and Depression Scale (HADS) is a brief, self-administered questionnaire for the assessment of anxiety and depression in hospital patients. A recent review [7] discussed the disagreement among different studies with respect to the dimensionality of the HADS, leading Coyne and Van Sonderen [8] to conclude from this disagreement that the HADS must be abandoned. Our study argues that the disagreement is mainly due to a methodological artifact, and that the HADS needs revision rather than abandonment.MethodWe used Mokken scale analysis (MSA) to investigate the dimensionality of the HADS items in a representative sample from the Dutch non-clinical population (N = 3643) and compared the dimensionality structure with the results that Emons, Sijtsma, and Pedersen [11] obtained in a Dutch cardiac-patient sample.ResultsWe demonstrated how MSA can retrieve either one scale, two subscales, or three subscales, and that the result not only depends on the data structure but also on choices that the researcher makes. Two 5-item HADS scales for anxiety and depression seemed adequate. Four HADS items constituted a weak scale and contributed little to reliable measurement.ConclusionsWe argued that several psychometric methods show only one level of a hierarchical dimensionality structure and that users of psychometric methods are often unaware of this phenomenon and miss information about other levels. In addition, we argued that a theory about the attribute may guide the researcher but that well-tested theories are often absent.Keywords: Anxiety, Depression, Dimensionality, HADS, Mokken scale analysis

An improved whole cell pertussis vaccine, designated as Plow, which is low in endotoxicity due to a chemical extraction of lipo-oligosaccharide (LOS) from the outer membrane, was evaluated for safety, immunogenicity and potency, comparatively to a traditional whole cell pertussis vaccine. Current whole cell pertussis vaccines are effective but contain large quantities of endotoxin and consequently display local and systemic adverse reactions after administration. Endotoxin is highly inflammatory and contributes considerably to the reactogenicity as well as the potency of these vaccines. In contrast, acellular pertussis vaccines hardly contain endotoxin and are significantly less reactogenic, but their elevated costs limit their global use, especially in developing countries. In this paper, bulk products of Plow and a traditional whole cell vaccine, formulated as plain monocomponents or combined with diphtheria and tetanus toxoids (DTPlow or DTP, respectively) were compared by in vitro and in vivo assays. Chemical extraction of LOS resulted in a significant decrease in endotoxin content (20%) and a striking decline in endotoxin related toxicity (up to 97%), depending on the used in vitro or in vivo test. The LOS extraction did not affect the integrity of the product and, more importantly, did not affect the potency and/or stability of DTPlow. Moreover, hardly any differences in antibody and T-cell responses were observed. The development of Plow is a significant improvement regarding the endotoxicity of whole cell pertussis vaccines and therefore a promising and affordable alternative to currently available whole cell or acellular pertussis vaccines for developing countries.

Mokken scale analysis is a popular method for scaling dichotomous and polytomous items. Whether or not items form a scale is determined by three types of scalability coefficients: (1) for pairs of items, (2) for items, and (3) for the entire scale. It has become standard practice to interpret the sample values of these scalability coefficients using Mokken’s guidelines, which have been available since the 1970s. For valid assessment of the scalability coefficients, the standard errors of the scalability coefficients must be taken into account. So far, standard errors were not available for scales consisting of Likert items, the most popular item type in sociology, and standard errors could only be computed for dichotomous items if the number of items was small. This study solves these two problems. First, we derived standard errors for Mokken’s scalability coefficients using a marginal modeling framework. These standard errors can be computed for all types of items used in Mokken scale analysis. Second, we proved that the method can be applied to scales consisting of large numbers of items. Third, we applied Mokken scale analysis to a set of polytomous items measuring tolerance. The analysis showed that ignoring standard errors of scalability coefficients might result in incorrect inferences.Keywords: Mokken scale analysis, standard errors, scalability coefficients, marginal models.

We discuss the statistical testing of three relevant hypotheses involving Cronbach's alpha: one where alpha equals a particular criterion; a second testing the equality of two alpha coefficients for independent samples; and a third testing the equality of two alpha coefficients for dependent samples. For each of these hypotheses, various statistical tests have been proposed. Over the years, these tests have depended on progressively fewer assumptions. We propose a new approach to testing the three hypotheses that relies on even fewer assumptions, is especially suited for discrete item scores, and can be applied easily to tests containing large numbers of items. The new approach uses marginal modelling. We compared the Type I error rate and the power of the marginal modelling approach to several of the available tests in a simulation study using realistic conditions. We found that the marginal modelling approach had the most accurate Type I error rates, whereas the power was similar across the statistical tests.

Obesity and type 2 diabetes are associated with low-grade inflammation and specific changes in gut microbiota composition. We previously demonstrated that administration of Akkermansia muciniphila to mice prevents the development of obesity and associated complications. However, the underlying mechanisms of this protective effect remain unclear. Moreover, the sensitivity of A. muciniphila to oxygen and the presence of animal-derived compounds in its growth medium currently limit the development of translational approaches for human medicine. We have addressed these issues here by showing that A. muciniphila retains its efficacy when grown on a synthetic medium compatible with human administration. Unexpectedly, we discovered that pasteurization of A. muciniphila enhanced its capacity to reduce fat mass development, insulin resistance and dyslipidemia in mice. These improvements were notably associated with a modulation of the host urinary metabolomics profile and intestinal energy absorption. We demonstrated that Amuc-1100, a specific protein isolated from the outer membrane of A. muciniphila, interacts with Toll-like receptor 2, is stable at temperatures used for pasteurization, improves the gut barrier and partly recapitulates the beneficial effects of the bacterium. Finally, we showed that administration of live or pasteurized A. muciniphila grown on the synthetic medium is safe in humans. These findings provide support for the use of different preparations of A. muciniphila as therapeutic options to target human obesity and associated disorders.

Objective: To investigate the relationships of attachment security and mentalization with core and co-morbid symptoms in eating disorder patients. Method: We compared 51 eating disorder patients at the start of intensive treatment and 20 healthy controls on attachment, mentalization, eating disorder symptoms, depression, anxiety, personality disorders, psycho-neuroticism, autonomy problems and self-injurious behavior, using the Adult Attachment Interview, the SCID-I and II and several questionnaires. Results: Compared with the controls, the eating disorder patients showed a higher prevalence of insecure attachment; eating disorder patients more often than controls received the AAI classification Unresolved for loss or abuse. They also had a lower level of mentalization and more autonomy problems. In the patient group eating disorder symptoms, depression, anxiety, psycho-neuroticism and autonomy problems were neither related to attachment security nor to mentalization; self-injurious behavior was associated with lesser attachment security and lower mentalization; borderline personality disorder was related to lower mentalization. In the control group no relations were found between attachment, mentalization and psychopathologic variables. Discussion: Eating disorder patients’ low level of mentalization suggests the usefulness of Mentalization Based Treatment techniques for eating disorder treatment, especially in case of self-injurious behavior and/or co-morbid borderline personality disorder.

This article first discusses a statistical test for investigating whether or not the pattern of missing scores in a respondent-by-item data matrix is random. Since this is an asymptotic test, we investigate whether it is useful in small but realistic sample sizes. Then, we discuss two known simple imputation methods, person mean (PM) and two-way (TW) imputation, and we propose two new imputation methods, response-function (RF) and mean response-function (MRF) imputation. These methods are based on few assumptions about the data structure. An empirical data example with simulated missing item scores shows that the new method RF was superior to the methods PM, TW, and MRF in recovering from incomplete data several statistical properties of the original complete data. Methods TW and RF are useful both when item score missingness is ignorable and nonignorable.

Outer Membrane Vesicles (OMVs) are gaining attention as vaccine candidates. The successful expression of heterologous antigens in OMVs, with the OMV functioning both as adjuvant and delivery vehicle, has greatly enhanced their vaccine potential. Since there are indications that surface exposed antigens might induce a superior immune response, targeting of heterologous antigens to the OMV surface is of special interest. Several systems for surface display of heterologous antigens on OMVs have been developed. However, these systems have not been used to display lipidated membrane-associated proteins known as lipoproteins, which are emerging as key targets for protective immunity. We were therefore interested to see whether we could express a foreign lipoprotein on the outer surface of OMVs. When outer surface protein A (OspA), a borrelial surface-exposed lipoprotein, was expressed in meningococci, it was found that although OspA was present in OMVs, it was no longer surface-exposed. Therefore, a set of fusions of OspA to different regions of factor H binding protein (fHbp), a meningococcal surface-exposed lipoprotein, were designed and tested for their surface-exposure. An N-terminal part of fHbp was found to be necessary for the successful surface display of OspA on meningococcal OMVs. When mice were immunized with this set of OMVs, an OspA-specific antibody response was only elicited by OMVs with clearly surface-exposed OspA, strengthening the idea that the exact positioning of an antigen in the OMV affects the immune response. This method for the surface display of heterologous lipoproteins on OMVs is a step forward in the development of OMVs as a vaccine platform.

Akkermansia muciniphila colonizes the mucus layer of the gastrointestinal tract, where the organism can be exposed to the oxygen that diffuses from epithelial cells. To understand how A. muciniphila is able to survive and grow at this oxic-anoxic interface, its oxygen tolerance and response and reduction capacities were studied. A. muciniphila was found to be oxygen tolerant. On top of this, under aerated conditions, A. muciniphila showed significant oxygen reduction capacities and its growth rate and yield were increased compared to those seen under strict anaerobic conditions. Transcriptome analysis revealed an initial oxygen stress response upon exposure to oxygen. Thereafter, genes related to respiration were expressed, including those coding for the cytochrome bd complex, which can function as a terminal oxidase. The functionality of A. muciniphila cytochrome bd genes was proven by successfully complementing cytochrome-deficient Escherichia coli strain ECOM4. We conclude that A. muciniphila can use oxygen when it is present at nanomolar concentrations. IMPORTANCE This article explains how Akkermansia muciniphila , previously described as a strictly anaerobic bacterium, is able to tolerate and even benefit from low levels of oxygen. Interestingly, we measured growth enhancement of A. muciniphila and changes in metabolism as a result of the oxygen exposure. In this article, we discuss similarities and differences of this oxygen-responsive mechanism with respect to those of other intestinal anaerobic isolates. Taken together, we think that these are valuable data that indicate how anaerobic intestinal colonizing bacteria can exploit low levels of oxygen present in the mucus layer and that our results have direct relevance for applicability, as addition of low oxygen concentrations could benefit the in vitro growth of certain anaerobic organisms.