Unit-weighted scales imply models that should be tested!

In several studies unit-weighted sum scales based on the unweighted sum of items are derived from the pattern of salient loadings in confirmatory factor analysis. The problem of this procedure is that the unit-weighted sum scales imply a model other than the initially tested confirmatory factor model. In consequence, it remains generally unknown how well the model implied by the unit-weighted sum scales fits the data. Nevertheless, the derived unit-weighted sum scales are often used in applied settings. The paper demonstrates how model parameters for the unit-weighted sum scales can be computed and tested by means of structural equation modeling. An empirical example based on a personality questionnaire and subsequent unit-weighted scale analyses are presented in order to demonstrate the procedure. Accessed 6,132 times on https://pareonline.net from February 18, 2013 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

06172 Abstracts Collection -- Directed Model Checking

From 26.04.06 to 29.04.06, the Dagstuhl Seminar 06172 ``Directed Model Checking\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Concealing Untrustworthiness: The Role of Conflict Monitoring in a Social Deception Task

Deception studies emphasize the important role of event-related potentials (ERPs) to uncover deceptive behavior based on underlying neuro-cognitive processes. The role of conflict monitoring as indicated by the frontal N2 component during truthful and deceptive responses was investigated in an adapted Concealed Information Test (CIT). Previously memorized pictures of faces should either be indicated as truthfully trustworthy, truthfully untrustworthy or trustworthy while concealing the actual untrustworthiness (untrustworthy-probe). Mean, baseline-to-peak and peak-to-peak amplitudes were calculated to examine the robustness of ERP findings across varying quantification techniques. Data of 30 participants (15 female; age: M = 23.73 years, SD = 4.09) revealed longer response times and lower correct rates for deceptive compared to truthful trustworthy responses. The frontal N2 amplitude was more negative for untrustworthy-probe and truthful untrustworthy compared to truthful trustworthy stimuli when measured as mean or baseline-to-peak amplitude. Results suggest that deception evokes conflict monitoring and ERP quantifications are differentially sensitive to a-priori hypotheses

A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks

Counterexample-guided repair aims at creating neural networks with mathematical safety guarantees, facilitating the application of neural networks in safety-critical domains. However, whether counterexample-guided repair is guaranteed to terminate remains an open question. We approach this question by showing that counterexample-guided repair can be viewed as a robust optimisation algorithm. While termination guarantees for neural network repair itself remain beyond our reach, we prove termination for more restrained machine learning models and disprove termination in a general setting. We empirically study the practical implications of our theoretical results, demonstrating the suitability of common verifiers and falsifiers for repair despite a disadvantageous theoretical result. Additionally, we use our theoretical insights to devise a novel algorithm for repairing linear regression models based on quadratic programming, surpassing existing approaches.Comment: Accepted at ICML 2023. 9 pages + 13 pages appendix, 8 figure

symQV: Automated Symbolic Verification of Quantum Programs

We present symQV, a symbolic execution framework for writing and verifying quantum computations in the quantum circuit model. symQV can automatically verify that a quantum program complies with a first-order specification. We formally introduce a symbolic quantum program model. This allows to encode the verification problem in an SMT formula, which can then be checked with a delta-complete decision procedure. We also propose an abstraction technique to speed up the verification process. Experimental results show that the abstraction improves symQV's scalability by an order of magnitude to quantum programs with 24 qubits (a 2^24-dimensional state space).Comment: This is the extended version of a paper with the same title that appeared at FM 2023. Tool available at doi.org/10.5281/zenodo.740032

Determinants of Recognizing and Evaluating Object Types. A Linguistic-Differential- Psychological Study of the Genitive Case

It is self-evident that language changes across time; how this process of language change takes place has been investigated for specific domains, such as the genitive case. Language change may induce a heterogeneity of verbal compe- tences. However, in differential psychology theoretical models on verbal intelli- gence imply that verbal competence is a rather homogeneous. Accordingly, the question of homogeneity and heterogeneity of verbal competences is a rather open one. Therefore, this study investigates the competence of differentiating sentences with genitive verbs from other object types and of evaluating the familiarity with these object types. It was examined whether homogeneous or heterogeneous linguistic competences are relevant for the evaluation of the grammatical correctness of sentences. The methodological basis for the linguistic and differential psychological study was a questionnaire of 22 groups of senten- ces with verbs requiring the genitive as an object case and/or verbs requiring another object case. Participants (N = 177 students) were asked to evaluate the grammatical correctness of the sentences (correct vs. incorrect) and the familiarity of content of the sentences on a six point Likert scale. Based on a statistical method termed principal component analysis, the relevance of homogenous vs. heterogeneous linguistic competences was investigated. This analysis led to six principal components which can be differentiated with regard to their relevance for linguistic competences. In addition, it could be demonstrated that the mother tongue (German vs. non-German) and the course of study (German studies or Psychology) influenced the evaluation of correctness. The findings indicate that relations between specific linguistic competences and verbal intelligence should be analyzed with regard to language and socialization processes

Diagnosis, synthesis and analysis of probabilistic models

This dissertation considers three important aspects of model checking Markov models:\ud diagnosis — generating counterexamples, synthesis — providing valid parameter\ud values and analysis — verifying linear real-time properties. The three aspects are relatively\ud independent while all contribute to developing new theory and algorithms in the\ud research field of probabilistic model checking.\ud We start by introducing a formal definition of counterexamples in the setting of\ud probabilistic model checking. We transform the problem of finding informative counterexamples\ud to shortest path problems. A framework is explored and provided for\ud generating such counterexamples. We then investigate a more compact representation\ud of counterexamples by regular expressions. Heuristic based algorithms are applied to\ud obtain short regular expression counterexamples. In the end of this part, we extend\ud the definition and counterexample generation algorithms to various combinations of\ud probabilistic models and logics.\ud We move on to the problem of synthesizing values for parametric continuous-time\ud Markov chains (pCTMCs) wrt. time-bounded reachability specifications. The rates\ud in the pCTMCs are expressed by polynomials over reals with parameters and the\ud main question is to find all the parameter values (forming a synthesis region) with\ud which the specification is satisfied. We first present a symbolic approach where the\ud intersection points are computed by solving polynomial equations and then connected\ud to approximate the synthesis region. An alternative non-symbolic approach based on\ud interval arithmetic is investigated, where pCTMCs are instantiated. The error bound,\ud time complexity as well as some experimental results have been provided, followed by\ud a detailed comparison of the two approaches.\ud In the last part, we focus on verifying CTMCs against linear real-time properties\ud specified by deterministic timed automata (DTAs). The model checking problem aims\ud at computing the probability of the set of paths in CTMC C that can be accepted\ud by DTA A, denoted PathsC(A). We consider DTAs with reachability (finite, DTA♦)\ud and Muller (infinite, DTAω) acceptance conditions, respectively. It is shown that\ud PathsC(A) is measurable and computing its probability for DTA♦ can be reduced to\ud computing the reachability probability in a piecewise deterministic Markov process\ud (PDP). The reachability probability is characterized as the least solution of a system\ud of integral equations and is shown to be approximated by solving a system of PDEs.\ud Furthermore, we show that the special case of single-clock DTA♦ can be simplified to\ud solving a system of linear equations. We also deal with DTAω specifications, where the\ud problem is proven to be reducible to the reachability problem as in the DTA♦ case

Hyperarousal in the hospital and what to do about it:the MED-PSYCH-NET - a transitional network approach fostering personalized care in psychosomatic medicine

Psychosomatics offers new perspectives to different medical specialisations not usually working together. It is shown that psychosomatic care based on integrated collaboration has better results and provides more scientific insights. This dissertation describes the effects of a transmural medical- psychological network providing multidisciplinary care to patients with psychosomatic symptoms resistant to treatment based on monodisciplinary approaches. We studied direct outcome measures and socially relevant medical costs and cost savings. An alarm falsification model was presented describing the relationship between functional physical symptoms and accompanying emotional symptoms. We also introduced a method allowing the measurement of psychosomatic symptoms in daily life which improves the knowledge of how stress-related symptoms develop

Protocol verification with heuristic search

We present an approach to reconcile explicit state model checking and heuristic directed search and provide experimental evidence that the model checking problem for concurrent systems, such as communications protocols, can be solved more efficiently, since finding a state violating a property can be understood as a directed search problem. In our work we combine the expressive power and implementation efficiency of the SPIN model checker with the HSF heuristic search workbench, yielding the HSF-SPIN tool that we have implemented. We start off from the A* algorithm and some of its derivatives and define heuristics for various system properties that guide the search so that it finds error states faster. In this paper we focus on safety properties and provide heuristics for invariant and assertion violation and deadlock detection. We provide experimental results for applying HSF-SPIN to two toy protocols and one real world protocol, the CORBA GIOP protocol

Error-Related Negativity and the Misattribution of State-Anxiety Following Errors: On the Reproducibility of Inzlicht and Al-Khindi (2012)

In their innovative study, Inzlicht and Al-Khindi (2012) demonstrated that participants who were allowed to misattribute their arousal and negative affect induced by errors to a placebo beverage had a reduced error-related negativity (ERN/Ne) compared to controls not being allowed to misattribute their arousal following errors. These results contribute to the ongoing debate that affect and motivation are interwoven with the cognitive processing of errors. Evidence that the misattribution of negative affect modulates the ERN/Ne is essential for understanding the mechanisms behind ERN/Ne. Therefore, and because of the growing debate on reproducibility of empirical findings, we aimed at replicating the misattribution effects on the ERN/Ne in a go/nogo task. Students were randomly assigned to a misattribution group (n = 48) or a control group (n = 51). Participants of the misattribution group consumed a beverage said to have side effects that would increase their physiological arousal, so that they could misattribute the negative affect induced by errors to the beverage. Participants of the control group correctly believed that the beverage had no side effects. As Inzlicht and Al-Khindi (2012), we did not observe performance differences between both groups. However, ERN/Ne differences between misattribution and control group could not be replicated, although the statistical power of the replication study was high. Evidence regarding the replication of performance and the non-replication of ERN/Ne findings was confirmed by Bayesian statistics