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Presence of one or more outliers in the observations affect inference procedure in statistical analysis. Designs robust against presence of a single outlier can be found in the literature for both regression and block design set-ups. In this paper, an attempt has been made to find a robust design in a block design set-up for the estimation of a full set of orthonormal treatment contrasts when there are more than one outlier among the observations. It appears that symmetry and balance play an important role in this study; it is seen that as we deviate from them, designs deviate from robustness. [ABSTRACT FROM AUTHOR]

Consistency of word production contributes to carers' ability to understand children's speech. Reports of the proportion of words produced consistently by typically developing preschool children, however, vary widely from 17% to 87%. This paper examines the quantitative (consistency count) and qualitative (e.g. phonemic analysis) characteristics of word consistency in 96 children aged 36–60 months. Children named 15 pictures twice, in separate trials, in the same assessment session. The mean consistency of the production for the whole group was 82%. Older children were more consistent than younger children. Girls were more consistent than boys. Words produced correctly in one trial and in error in another may indicate resolving error patterns. Words produced in error in two different ways provided useful evidence about the nature of inconsistent word production in typically developing children. The clinical and theoretical implications are discussed. [ABSTRACT FROM AUTHOR]

The effect of nanosilica under the influence of dispersing agents on the fresh empirical and fundamental rheological properties of self-compacting concrete (SCC) is a complex phenomenon which has been investigated in this paper. Models to predict the rheological properties of nanosilica blended SCC are also lacking to avoiding/saving comprehensive and costly rheology laboratory trials mainly when these tests are unavailable or limited. To these ends, 315 laboratory tests were performed on 15 blended SCC mixtures, manufactured using five nanosilica dosages, 0%, 0.5%, 1%, 1.5%, 2%, and three dispersing superplasticizer dosages, 0.62%, 0.66%, 0.70%, by weight of cement. Fundamental rheological properties of the SCC mixes were assessed by using a rotational concrete rheometer based on the nonlinear modified Binghamian model. Results showed that SCC mixes are sensitive to nanosilica and superplasticizer admixtures producing a complex non-linear effect on their empirical and rheological properties. Based on these trends, eleven empirical models were proposed to predict the fresh empirical and rheological properties of the SCC mixes. A statistical analysis demonstrated the good fitting of the proposed models with the measured properties of SCC mixes during the laboratory trials. These models could serve for design and production of nanosilica blended SCC as alternative approach. [ABSTRACT FROM AUTHOR]

Estimation and prediction of regression models with partition forms are widely applied techniques in statistical inference and data analysis. In this paper, we consider some fundamental inference problems regarding a linear random-effects model (LREM) and its reduced models without statistical distribution assumptions for error terms. We shall present a partition form of LREM and its correctly-reduced models, introduce the consistency concepts of the LREM and its reduced models, define the predictability/estimability of unknown parameters in the LREM and its reduced models, establish the matrix equations and analytical formulas associated with best linear unbiased predictors (BLUPs) and best linear unbiased estimators (BLUEs) of all unknown parameter vectors in the LREM and its reduced models, and present many fundamental decomposition equalities for the BLUPs/BLUEs of all unknown parameters in the LREM and its reduced models. [ABSTRACT FROM AUTHOR]

The Foundations of Early Literacy Assessment – Northern Territory (FELA-NT) was funded, developed, and implemented as part of a strategy designed to address the English literacy learning needs of the Northern Territory's Aboriginal student population. In this paper we question whether the FELA-NT English literacy learning benchmarks are representative of remote and very remote Aboriginal students since many speak English as an Additional Language (EAL) or Dialect (EAD). Using a new data set of scores from 72 Aboriginal students from remote, very remote, and outer-regional communities on the FELA-NT, we demonstrate that it is the student's experience with Standard Australian English, not their remoteness, that impacts their early literacy development. We use this example to illustrate how current practices and policies homogenise the Australian Aboriginal student population, silencing linguistic diversity in the process. We call for clinical practitioners and educators to shift their practices to assessments and tools that recognise children and youths' diverse linguistic skills and pathways. We talk about what empowerment, participation, and inclusion might really mean in current Australian educational and clinical contexts. We argue here that we need to fundamentally rethink how we work with children with diverse language and literacy knowledge, skills, and backgrounds if we are to reduce inequalities (SDG 10), honour quality education (SDG 4), and support sustainable communities (SDG 11). [ABSTRACT FROM AUTHOR]

Analysis of covariance (ANCOVA) is a widely used statistical analysis technique in numerous experimental studies. The existing ANCOVA test cannot be applied when the sample is taken from a population with imprecise and uncertain data. Neutrosophic statistics will be employed when analyzing data containing uncertain observations. In this paper, we make a significant contribution by proposing a novel method for ANCOVA using neutrosophic statistics as an extension of the existing ANCOVA. This study applied the neutrosophic analysis of covariance (NANCOVA) in three different designs (neutrosophic completely randomized design (NCRD), neutrosophic randomized complete block design (NRCBD), and neutrosophic split-plot design (NSPD)). We have implemented and explained this method with numerical examples. According to our experimental results, the proposed NANCOVA method is flexible and effective in the presence of uncertainty compared to the existing method. [ABSTRACT FROM AUTHOR]

The aim of this paper is to research the impact of the tax system on SMEs inSerbia. A quantitative survey research was conducted, containing research questions referring to tax environment impact, its factors and incentives on growth. The sampling was purposive, and it consisted of responsible people in SMEs ( n = 117). The main attitude of our respondents and the conclusion of the research is that the level of tax bureaucracy, as well as unprofessional tax administration created an unstimulating tax environment for SMEs. Not only did this environment make no impact on gray economy and corruption reduction but also supported them. [ABSTRACT FROM AUTHOR]

Libraries are places where patrons find resources that can help them accomplish their information needs. One of the key elements of this need is being able to find what they are looking for. While much has been written about information seeking behavior and library wayfinding, however, there is a more fundamental argument. That is merely finding the item when the Library Management System says it should be on the shelf. In these little moments, the library has an opportunity to build a sense of trust with the patron. The patron can trust that an item that the library says is there, is there. It is also an opportunity for a library to have a small victory in a positive patron library experience. However, if the item is not there that small victory is squandered. The challenge though is large scale shelf checks for shelving integrity is cost and time prohibitive. What is needed is a quick way to determine library and catalog health. This paper will demonstrate how this can be accomplished by looking at the ILL statistics. While this may seem like a simple answer demonstrating it with statistical relationships confirms what many libraries may view as a forgone assumption. [ABSTRACT FROM AUTHOR]

This paper explores the nature of copula omission in Cypriot Greek individuals with Down Syndrome (DS). Previous studies on DS have attributed high rates of copula omission to an overall grammatical/inflectional impairment without offering further analysis. In order to identify relevant conditioning factors, we examined copula productions and omissions from spontaneous and elicited experimental tasks under five levels of analysis: categorial type of the predicate (nominal vs. adjectival), aspectual interpretation of the predicate (permanent vs. temporary), and a combination of these first two, as well as subject status (overt vs. covert) and experimental design (spontaneous vs. elicited). Results showed that adults with DS had significantly higher rates of copula omission than TD children. We found subject overtness to be the most reliable predictor of copula omission. A comparison of the two experimental methods of data collection also revealed a significant effect. Following an analysis based on the Unique Checking Constraint, we propose that copula omission is facilitated by the restriction that only one EPP feature (either the one in TP or the one in TopicP) can be checked. We discuss the implications of these results in the context of a distinction across a delayed vs. deviant development of the DS grammar. [ABSTRACT FROM AUTHOR]

The difficulties economists have in conducting laboratory experiments necessitates much of their applied analysis being based on numerous quasi-experiments conducted under a variety of uncontrolled conditions. The result is the need to synthesis these results if any generally useful parameters are to be found for such things as value transfers or policy assessments in transportation. The paper reviews some of the issues involved in using meta-analysis to conduct statistical analysis of such previous quantitative work in transportation economics, examines the success that more recent meta studies have had in overcoming earlier criticisms of the methodology, and sets this in the contexts of on-going developments in meta-analysis more generally. The paper suggests ways that meta-analytics can address some remaining issues. [ABSTRACT FROM AUTHOR]

In this work, students’ thinking modes and representation types in linear algebra are investigated through statistical implicative analysis techniques. Specifically, our research question considers the implicative relationships between students’ thinking modes and representation types of linear algebra. The participants were 74 undergraduate linear algebra students enrolled in the department of mathematics education of a government university located in western Turkey. The data was collected using six paper-and-pencil tasks, relating to a context of linear equations, matrix algebra, linear combination, span, linear independency-dependency and basis. A document analysis technique was used to analyze the data within a theoretical lens of thinking modes and representation types. To delineate similarity diagrams, hierarchical trees, and implicative models (which will be detailed in the paper), an R version of Cohesion Hierarchical Implicative Classification software was used. According to the results, students’ analytic structural thinking modes on linear combination and span and linear independency significantly imply the use of algebraic and abstract representations. The results also confirm that the notions of linear combination and span and linear dependency/independency are core elements for theoretical thinking and are needed for learning linear algebra. [ABSTRACT FROM AUTHOR]

The article discusses the paper entitled "The Statistical Evaluation of Categorical Measurements: Simple Scales, but Treacherous Complexity Underneath," by Jeroen de Mast and colleagues. It says that the paper evokes awareness of the complexity underlying the categorical or binary measurement system. It states that the paper has given an account on the use of kappa statistics on several fields, including psychometrics, medicine, and manufacturing.

The Group Selection problem is an essential problem in the supplier selection process. The objective of the problem is to select a subset of suppliers containing the best among multiple candidate suppliers. Manufacturers should procure parts from the selected suppliers to produce high-quality products. Lin, C.J., W.L. Pearn, J.Y. Huang, and Y.H. Chen [2017. "Group Selection for Processes with Multiple Quality Characteristics." Communications in Statistics - Theory and Methods. doi:10.1080/03610926.2017.1364392] considered the problem under multiple quality characteristics, and proposed the Modified Bonferroni method and the Multiple Comparisons with the Best (MCB) method to tackle the problem. The two methods, however, may select different subset containing the best depending on the magnitude of the differences among the k estimated index values. In this paper, we derive the power function for the Modified Bonferroni method, and compare the power of the two methods with extensive simulations. The results show that the MCB method is more powerful than the Modified Bonferroni method when the actual number of the best process is one. On the other hand, the Modified Bonferroni method significantly outperforms the MCB method when the actual number of the best process is greater than one. The results provide practitioners with useful reference about the properties of the two methods for supplier selection. [ABSTRACT FROM AUTHOR]

Smart warehouse automation has emerged as an effective, competitive solution for suppliers and distributors. With the increasing demand for physical storage and distribution services, suppliers and service providers are challenged to respond not only effectively, but with minimal latency. Differentiated service levels for different classes of customer orders have not yet, however, been developed for physical storage and retrieval. In this paper, in the context of smart warehouse automation services, a novel policy, called Differentiated Probabilistic Queuing (DPQ) is developed for servicing customers' orders by Automated Guided Vehicles (AGV). Applying the DPQ policy, the average overall latency of each customer order, the mean overall processing time of this customer's orders in the smart warehouse automation system, is characterised under Poisson customer order arrival patterns. The weighted average latency of all customer orders is optimised over the choice of (1) storage assignment and (2) DPQ policy. Due to the existence of two types of variables, Alternating Minimisation method is applied to solve this joint optimisation problem. Compared with a combination of the classical turn-over rate storage assignment method and FCFS policy, the new approach yields 19.64% lower (better) objective function value with statistical significance. Numerical analysis results also indicate, as expected, that when the smart warehouse system resources become more limited, and the price difference among different classes of customer orders increases, the improvement becomes even more significant. [ABSTRACT FROM AUTHOR]

The main object of investigation in this paper is a very general regression model in optional setting – when an observed process is an optional semimartingale depending on an unknown parameter. It is well known that statistical data may present an information flow/filtration without 'usual conditions'. The estimation problem is achieved by means of structural least squares (LS) estimates and their sequential versions. The main results of the paper are devoted to the strong consistency of such LS-estimates. For sequential LS-estimates, the property of fixed accuracy is proved. Finally, several illustrative examples from risk theory and mathematical finance are presented. [ABSTRACT FROM AUTHOR]

To investigate determinants of willingness to adopt telerehabilitation, willingness of technology use, core affect regarding using telerehabilitation, and digital competencies in rehabilitation professionals in Austria and Germany before and during the COVID-19 pandemic. A cross-sectional paper-based and online survey was conducted before and during COVID-19, respectively, with three cohorts of rehabilitation professionals. Outcomes were the willingness to adopt telerehabilitation evaluated using the extended Unified Theory of Acceptance and Use of Technology; willingness of technology use using the short scale for assessing the willingness of technology use; digital competencies and core affect using the Digital Competence Framework and semantic differential, respectively. Multivariate ordinal regression analysis was performed to determine predictors. Included were 603 rehabilitation professionals. Analysis revealed differences between Austria and Germany and before and during the pandemic for most outcomes. German residency, the pandemic, and a higher educational level were most important predictors of higher willingness to adopt telerehabilitation, willingness of technology use, digital competencies, and positive core affect. The pandemic increased most aspects of willingness to adopt telerehabilitation, willingness of technology use, digital competencies, and positive core affect. Results confirm that rehabilitation professionals with higher degrees are more prone to adopt innovations in healthcare.Registration: German Clinical Trials Register (DRKS00021464) The willingness to adopt telerehabilitation is associated with external factors increasing the need for alternative rehabilitation delivery, such as COVID-19, and with financial facilitators, such as reimbursement. As the willingness to adopt telerehabilitation is higher among speech and language therapists and dietitians, efforts are necessary to enhance its use in physiotherapists and occupational therapists. As a higher willingness to adopt telerehabilitation was observed in younger rehabilitation professionals and those with higher education, increasing the importance of telerehabilitation in education curricula and further knowledge transfer into practice for those already working in the field seems necessary. [ABSTRACT FROM AUTHOR]

An acute difficulty in wine-ratings-related research, and in calculating consensus among judges, is that each rating is one observation drawn from a latent probability distribution that is wine- and judge-specific. One observation is almost no data at all. Minimizing a weighted sum of cross entropies has been proposed as a method of estimating the shape of the latent distribution using one observation. That method was tested on 30 blind triplicate wine ratings. This article replicates that test, presents results of tests at hypothetical boundary conditions, and then presents test results for a set of 30 blind triplicate ratings published by Cicchetti [(2014, August). Blind tasting of South African wines: A tale of two methodologies (AAWE Working Paper No. 164, 15 pages)] and a set of 1599 blind triplicate ratings from the California State Fair. The test results show that the minimum cross entropy solution is substantially more accurate than the analysis of a single rating. [ABSTRACT FROM AUTHOR]

Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this paper, we obtain explicit expressions for the Fisher information matrix in ranked set sampling (RSS) from the simple linear regression model with replicated observations. It has been shown to be the sum of two matrices, one of which is the Fisher information matrix based on simple random sampling (SRS). The numerical results show that RSS provides more information than SRS when the same sample size is used. [ABSTRACT FROM AUTHOR]

In many statistical analysis, a finite population may contain a large proportion of zero-and-one values that make the population distribution severely skew. Confidence intervals based on a normal approximation (NA) for such data may have low coverage probabilities. In this paper, we apply the methods of jackknife empirical likelihood (JEL) and adjusted jackknife empirical likelihood (AJEL) to discuss the confidence intervals for the mean of zero-and-one inflated population. Asymptotic distributions of the likelihood-type statistics are studied. Simulations are conducted to compare coverage probabilities with other methods under different distributions. Real data is given to illustrate the procedure of proposed methods. [ABSTRACT FROM AUTHOR]

Objective: Iverson (2001) expanded on reliable change methodology by accounting for the variability in scores at Time 2 in the calculation of change scores. However, due to limitations in available data, an incomplete picture of variables affecting change was presented. The current paper sought to address some of these limitations and clarify the methodology for assessing reliable change. Method: Using one-year test-retest data on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in older adults who were cognitively intact or had mild Alzheimer's disease (AD), change scores were calculated, and various models, consistent with or divergent from Iverson, were presented. Results: Across the RBANS, individuals with intact cognition tended to show less variable scores, especially at Time 2, which resulted in larger change scores than those with AD. When applied to an independent sample, different patterns of change were observed, with: (1) models that used intact data showed more cognitive change than those using AD data; (2) the model that corrected for practice effects and used intact data showed the most decline; and (3) the model that corrected for practice effects and used AD data showed the most improvement. The models that showed the strongest association in classifying independent cases as decline/stable/improve were those that used intact data and were discordant on the use of practice effects. Conclusions: Overall, findings highlight the complexity of calculating reliable change, and they lend additional caution to Iverson's original limitations. However, the use of data from individuals classified as cognitively intact and a correction for practice effects seems warranted. [ABSTRACT FROM AUTHOR]

Purpose: The present article summarises the characteristics of Rasch's theory, providing an original metrological model for persons' measurements. Properties describing the person "as a whole" are key outcome variables in Medicine. This is particularly true in Physical and Rehabilitation Medicine, targeting the person's interaction with the outer world. Such variables include independence, pain, fatigue, balance, and the like. These variables can only be observed through behaviours of various complexity, deemed representative of a given "latent" person's property. So how to infer its "quantity"? Usually, behaviours (items) are scored ordinally, and their "raw" scores are summed across item lists (questionnaires). The limits and flaws of scores (i.e., multidimensionality, non-linearity) are well known, yet they still dominate the measurement in Medicine. Conclusions: Through Rasch's theory and statistical analysis, scores are transformed and tested for their capacity to respect fundamental measurement axioms. Rasch analysis returns the linear measure of the person's property ("ability") and the item's calibrations ("difficulty"), concealed by the raw scores. The difference between a person's ability and item difficulty determines the probability that a "pass" response is observed. The discrepancy between observed scores and the ideal measures (i.e., the residual) invites diagnostic reasoning. In a companion article, advanced applications of Rasch modelling are illustrated. Questionnaires' ordinal scores are poor approximations of measures. The Rasch analysis turns questionnaires' scores into interval measures, provided that its assumptions are respected. Thanks to the Rasch analysis, accurate measures of independence, pain, fatigue, cognitive capacities and other whole person's variables of paramount importance in rehabilitation are available. The current work is addressed to rehabilitation professionals looking for an introduction to interpreting published results based on Rasch analysis. The first of a series of two, the present article illustrates the most common graphic and numeric outputs found in published papers presenting the Rasch analysis of questionnaires. [ABSTRACT FROM AUTHOR]

This study presents a method for analysing badminton matches based on the concept of perturbations. We transfer this principle to a badminton rally and describe the decisive shot, which turns a balanced situation into an advantage for one team or one player. Our paper proposes an observational system, which models the decisive shots by using four consecutive actions: impulse (the perturbation), follow-up, survival, and convert. To test the objectivity of the operationalization, independent raters analysed six matches in the singles disciplines of the 2022 World Championships. To evaluate rater agreement, Jaccard coefficient and Cohen's kappa were used. Results show an agreement in identifying impulses of J(R1, R2) =.80, while the agreement in classifying the impulse type (positive/negative) reached κ =.70. A comparison of this perturbation-based analysis and last shot analyses shows significantly different results. Direct errors usually occur in the midcourt (56.4%), whereas most negative perturbations originate from the backcourt (40.0%). In contrast to direct winners, mostly originating from a smash (45.5%), most positive perturbations are created by net shots (30.1%). We argue that our method can be complementary to common last shot analyses and provides a possibility to describe players' strengths and weaknesses in more detail. [ABSTRACT FROM AUTHOR]

To systematically review literature on nutritional intake, nutritional status and nutritional interventions, and to study their association with short- and long-term clinical outcomes in people with a major dysvascular lower limb amputation. PubMed, Ovid, CINAHL, and The Cochrane Library were searched. Studies were included if nutritional intake, nutritional status, or nutritional interventions in people with a major dysvascular lower limb amputation were analyzed. Of the 3038 unique papers identified, 30 studies were included. Methodological quality was moderate (1 study) or weak (29 studies). Limited information was available on nutritional intake (2 studies) and nutritional interventions (1 study). Nutritional intake and nutritional status were assessed by diverse methods. The percentage of people with a poor nutritional status ranged from 1% to 100%. In some studies, measures of poor nutritional status were associated with adverse short- and long-term clinical outcomes. The percentage of people with a poor nutritional status is inconclusive in the major dysvascular lower limb amputation population, because of the heterogeneity of the assessment methods used. Some included studies reported a negative association between poor nutritional status and clinical outcomes. However, these results should be interpreted with caution, because of the limited quality of the studies available. Studies high in methodological quality and high in hierarchy of evidence are needed. The proportion of people with a poor nutritional status in the major dysvascular lower limb amputation population is inconclusive. Poor nutritional status seems to affect clinical outcomes negatively. More uniformity in assessment of malnutrition in the major dysvascular lower limb amputation population is needed. [ABSTRACT FROM AUTHOR]

One of the key decisions in execution strategies is the choice between a passive (liquidity providing) or an aggressive (liquidity taking) order to execute a trade in a limit order book (LOB). Essential to this choice is the fill probability of a passive limit order placed in the LOB. This paper proposes a deep learning method to estimate the filltimes of limit orders posted in different levels of the LOB. We develop a novel model for survival analysis that maps time-varying features of the LOB to the distribution of filltimes of limit orders. Our method is based on a convolutional-Transformer encoder and a monotonic neural network decoder. We use proper scoring rules to compare our method with other approaches in survival analysis, and perform an interpretability analysis to understand the informativeness of features used to compute fill probabilities. Our method significantly outperforms those typically used in survival analysis literature. Finally, we carry out a statistical analysis of the fill probability of orders placed in the order book (e.g. within the bid-ask spread) for assets with different queue dynamics and trading activity. [ABSTRACT FROM AUTHOR]

The extropy measure proposed by Lad, Sanfilippo, and Agro (Statistical Science 30 (1):40–58, 2015) as a dual function of Shannon entropy has received a considerable attention in the last five years. In this paper, we first show a representation for the weighted extropy of ranked set sampling in terms of quantile and density-quantile functions. Then we provide some related results including monotone properties, stochastic orders, characterizations and sharp bounds. Moreover, the so obtained results show how the weighted extropy of ranked set sampling compares with its counterpart of simple random sampling. [ABSTRACT FROM AUTHOR]

This study investigates whether people's responses to official communications about COVID-19 could be "profiled" with respect to socio-economic-demographic and behavioral characteristics. Such profiles could enhance the effectiveness of future crisis management through the use of profile-adapted communications that maximize message comprehension. A representative web panel survey (742 respondents) was conducted across Switzerland in February 2022 to assess the population's reaction to COVID-19 communications during the pandemic. Latent profile analysis was conducted to explore if distinct profiles of reactions to the communications would emerge, and how each of them relate to conspiracy mentality and SED measures. The analyses revealed three latent profiles: "Compliant supporters" (54%), "defiant deniers" (23.6%), and "anxious skeptics" (22.4%). Respondents with high conspiracy mentality were more likely to belong to "defiant deniers" or "anxious skeptics." Each profile was characterized by distinct SED and behavioral features (discussed in the paper). The COVID-19 pandemic demonstrated that one communication does not work for all people. Our study evidenced three different types of respondent profiles that require profile-adapted communications for more effective crisis control. Our study is the first to profile people's responses to COVID-19 communications in a systematic, person-centered way. The results can be used for more effective future crisis management that delivers to each profile's communicative needs. [ABSTRACT FROM AUTHOR]

Game-based learning (GBL) is widely utilised in various domains and continues to receive interest and attention from researchers and practitioners alike. However, there is still a lack of empirical evidence concerning its effectiveness, making GBL evaluation a critical undertaking. This paper proposes an integrated approach for planning and executing GBL evaluation studies and presents its application by evaluating the effectiveness of a GBL approach to improve the Arabic reading skills of migrant refugee children in an informal learning setup. The study focuses on how children's age group, learning modality preference, and prior mobile experience affect their learning, usability, and gameplay performance. A quasi-experiment with a one-group pretest-posttest design was conducted with 30 children (5–10 years old) from migrant refugee backgrounds. The results show a statistically significant improvement in their reading assessment score. The results also outline a clear impact of children's age groups on their learning gain, usability score, and total levels played. Moreover, learning modality preference and prior mobile experience both had a statistically significant effect related to usability and gameplay performance parameters. However, no effect was found on learning gain. Based on the findings, some design recommendations are suggested for more inclusive design focusing on user characteristics. [ABSTRACT FROM AUTHOR]

Studies have shown that stress has contributed to employee turnover and retention problems for agencies, and at the individual level, chronic stress has been associated with coronary heart disease, anxiety, depression, and many other negative effects. In the past, the extent of stress one has felt has been measured by subjective paper-and-pencil instruments; however, recent technological advances have improved our ability to obtain accurate biofeedback assessments from wearable instruments. The Kentucky Child Welfare Workforce Wellness Initiative is the first known study to explore physiological stress in a sample (n = 32) of child welfare professionals using biometric technology (Firstbeat Bodyguard 2) and the first to report that data longitudinally over a four-month period. The study revealed that a variable associated with the strength of the Autonomic Nervous System (RMSSD) remained below the norms for a healthy population as participants experienced consistent and prolonged physiological stress. When examined relatively to the agency's lifting of COVID restrictions and returning to face-to-face service delivery, stress levels began to further rise almost to significant levels (p <.10) and the participants' ability to achieve a state of physiological relaxation significantly decreased. Future research employing biometric technology is also suggested. [ABSTRACT FROM AUTHOR]

Adolescent suicide has become an increasingly serious social problem in China. Bullying victimization was found to be an influential factor of suicidal tendency, but less attention has been paid to the internal mechanisms of the relationship. This paper examined the relationship between adolescents' bullying victimization and suicidal tendency, and the mediating effects of internalizing problems and non-suicidal self-injury (NSSI). Generalized Structural Equation Model was employed to a sample of 3,575 Chinese secondary school students. Bullying victimization has a direct positive impact on adolescents' suicidal tendency, but also has an indirect impact on suicidal tendency through three paths: the independent mediating role of internalizing problems and NSSI, and the chain mediating role of internalizing problems and NSSI. The results suggested that students who are bullied tend to have a higher risk of suicidal tendency, and internalizing problems and NSSI are usually the prelude to suicidal behaviors. [ABSTRACT FROM AUTHOR]

To examine the associations between psychological factors (pain catastrophizing, pain-related anxiety, and fear of pain) and level of pain and disability in patients with complex regional pain syndrome (CRPS). One hundred and two patients with CRPS were recruited from tertiary care centers with the different upper limb injuries were evaluated for pain, disability, and psychological factors. Patients completed the Disabilities of the Arm, Shoulder, and Hand (DASH) Questionnaire, Patient Rated Wrist Evaluation (PRWE), Pain Catastrophizing Scale (PCS), Tampa Scale of Kinesiophobia (TSK-11), and Depression, Anxiety, and Stress Scale (DASS). The associations of pain and disability with presence of these behavioral and mental health factors were examined using bivariate and multivariable analyses. These models were adjusted for age, sex, injured dominant hand, and previous surgery. A higher pain catastrophizing score (β = 0.55, p = 0.00) was associated with greater disability. A higher pain catastrophizing score (β = 0.35, p = 0.001) and female gender (β = 0.24, p = 0.01) were associated with greater pain at rest (PAR). A higher pain catastrophizing score and having a surgical history were associated with greater pain with movement (β = 0.25, p = 0.02). Scores of ≥18.5 in PCS, ≥57.5 on TSK, and ≥15.5 on DASS were associated with higher risk of experiencing pain and disability. Pain catastrophizing, female sex, and surgical intervention are associated with poor outcomes. Physiologic, psychological factors, and treatment factors interact to influence outcomes. The results of this study further validate the associations of chronic pain and disability with pain catastrophizing in patients with CRPS. The novel finding of this study is introducing cut-off scores for TSK, PCS, and DASS as a screening tool to predict pain, functional limitations. Pain catastrophizing has a vital role in the magnitude of disability and pain in patients with CRPS. The novel finding of this paper was the cut-off scores on the psychological evaluations that can enable using them as screening tool for bad outcomes in patients with CRPS. Cut off scores from different psychological evaluations can be used as a yellow flag for clinician's for detecting patients with increased risk of pain and disability. The identification of a cut-off can also have implications for implementing change in clinical practice by identifying the need for early and intensive interventions. [ABSTRACT FROM AUTHOR]

Researchers in statistical shape analysis often analyze outlines of objects. Even though these contours are infinite-dimensional in theory, they must be discretized in practice. When discretizing, it is important to reduce the number of sampling points considerably to reduce computational costs, but to not use too few points so as to result in too much approximation error. Unfortunately, determining the minimum number of points needed to achieve sufficiently approximate the contours is computationally expensive. In this paper, we fit regression models to predict these lower bounds using characteristics of the contours that are computationally cheap as predictor variables. However, least squares regression is inadequate for this task because it treats overestimation and underestimation equally, but underestimation of lower bounds is far more serious. Instead, to fit the models, we use the LINEX loss function, which allows us to penalize underestimation at an exponential rate while penalizing overestimation only linearly. We present a novel approach to select the shape parameter of the loss function and tools for analyzing how well the model fits the data. Through validation methods, we show that the LINEX models work well for reducing the underestimation for the lower bounds. [ABSTRACT FROM AUTHOR]

According to the World Health Organization, intimate partner violence (IPV) affects 35% of women worldwide and 40% of pregnant women, often resulting in maternal and infant death and harm. Displaced persons are at higher risk of abuse compared to the general population. While few studies have explored IPV in Iraq, research from Erbil, Iraq showed nearly 60% of women reported experiencing IPV in their lifetime. No publications examining IPV among displaced women in Iraq exist. Considering the severe impacts of IPV in pregnancy and the associated risks for IPV among women in refugee camps, this paper presents the first analysis of prevalence and factors associated with lifetime IPV among displaced pregnant women in two Iraqi refugee camps. Thirteen percent of women reported experiencing any abuse and experiencing IPV was associated with receiving fewer years of schooling (p = 0.04), not having a private doctor (p = 0.002), attending the first prenatal visit during the third trimester (p = 0.03), feeling pressure to have a child (p = 0.003), knowing someone who was physically injured by their husband (p = 0.05), experiencing suicidal ideation (p = 0.02), and being worried about harming one's baby (p = 0.02). Policy and programme recommendations for screening and prevention of IPV in resource-limited settings are provided. [ABSTRACT FROM AUTHOR]

In this paper, we consider the dynamical behaviour of a stochastic coronavirus (COVID-19) susceptible-infected-removed epidemic model with the inclusion of the influence of information intervention and Lévy noise. The existence and uniqueness of the model positive solution are proved. Then, we establish a stochastic threshold as a sufficient condition for the extinction and persistence in mean of the disease. Based on the available COVID-19 data, the parameters of the model were estimated and we fit the model with real statistics. Finally, numerical simulations are presented to support our theoretical results. [ABSTRACT FROM AUTHOR]

A comprehensive statistical analysis of energy poverty indicators is undertaken in the present paper, in an attempt to further understand the roots and results of the problem in Greece. Specifically, time-series data sets were analysed using various objective indicators, i.e. 10%, 2M, 2M EXP, M/2, M/2 EXP, as well as subjective indicators. Chi-square tests of Independence were performed and binary logistic regression models were developed to predict energy poverty (indicators of 10%, 2M and M/2), based on critical socio-economic factors. The logit model based on the 10% indicator presented the highest performance, reaching 32%. According to this model, the types of households mostly exposed to energy poverty were single families with dependent children and households located in Macedonia, increasing the relative probability of energy poverty by 7.0 and 6.5 times per unit, respectively. The outcomes derived can help policy-makers towards designing more targeted policies for tackling energy poverty in Greece. [ABSTRACT FROM AUTHOR]

This paper explores the associations between different types of social capital and other measures including wellbeing, school connectedness, and pragmatic language. Seventeen adolescents who were deaf or hard of hearing (DHH) from Australia and the United Kingdom completed an online survey and their results were analysed to answer research questions relating to: social capital formation in adolescents who are DHH; associations between social capital, wellbeing, pragmatics, and school connectedness; and the role of identity in social capital formation. Statistical analyses were completed to determine: bivariate correlations between variables; significant differences between the types of social capital measured; and significant differences in social capital according to identity group. Results indicate that overall, adolescents had higher Offline social capital compared to Online social capital, and higher Family social capital in comparison to Peer and Institutional social capital. Additionally, all social capital except Online social capital had strong associations with wellbeing and school connectedness measures. Students who identified as deaf had statistically significant lower levels of social capital than those who identified as hard of hearing or hearing impaired, and bicultural; however, this result may be due to the composition of this small sample. This study indicates that social capital is associated with higher levels of wellbeing and school connectedness and demonstrates that school experiences play an important role in the formation of social capital for students who are DHH. [ABSTRACT FROM AUTHOR]

This paper presents a machine-learning-based method for evaluating the internal value of talent in any organization and for evaluating the salary criteria. The study assumes the design and development of a salary predictor, based on artificial intelligence technologies, to help determine the internal value of employees and guarantee internal equity in the organization. The aim of the study is to achieve internal equity, which is a critical element a that directly affects employees' motivation. We implemented and validated the method with 130 employees and more than 70 talent acquisition cases with a Basque technology research organization during the years 2021 and 2022. The proposed method is based on statistical data assessment and machine-learning-based regression. We found that while most organizations have established variables for job evaluation as well as salary increments for staff according to their contribution to the organization, only a few employ tools to support equitable internal compensation. This study presents a successful real case of artificial intelligence applications where machine learning techniques help managers make the most equitable and least biased salary decisions possible, based on data. [ABSTRACT FROM AUTHOR]

This paper presents models that correlate deflection basin parameters (DBP) with seed moduli, which are the input of the backcalculation processes. The models were obtained by means of statistical analyses of a set of DBPs for different pavement structures. The proposed equations showed potential and increased accuracy in the estimation of seed moduli, since these are derived from DBP-based models that consider the deflection basin geometry. To evaluate the effectiveness of the models, they were applied to pavements located in five regions of Brazil, and a good approximation between the values of the seed and backcalculated moduli was observed. Therefore, there was less computational effort in the backcalculation process, since the closeness between the values of the moduli reduced the amount of iterations required. In pavements with different structures and boundary conditions, the methodology can be used to achieve more refined results. [ABSTRACT FROM AUTHOR]

Bayesian methods are often suggested as a solution for issues encountered in small sample research, however, Bayesian methods often require informative priors to outperform classical methods in these settings. Specifying accurate priors with respect to the true value of the parameter of interest is challenging and inaccurate informative priors can have detrimental effects on conclusions from the statistical analysis. This paper proposes an objective procedure for creating informative priors for mediation analysis based on a historical data set; the only requirements for implementing the procedure are that the data from the current study constitute a representative sample from the population of interest, and that the historical and current data sets contain measures of the same covariates and independent variable, mediator, and outcome. The simulation study findings show that the proposed method leads to appropriate amount of borrowing from the historical data set, which leads to increases in precision and power when the historical data and current data are exchangeable, and does not induce bias when the historical and current studies are not exchangeable. The proposed method is illustrated using data from the project PROsetta Stone, and we provide rstan code for implementing the proposed method. [ABSTRACT FROM AUTHOR]

The importance of ethics education for undergraduate engineering students has been emphasized due to the manifold impacts of engineering on society. However, little is known about moral disengagement among engineering students, which could potentially lead to unethical engineering practice. Especially, it is not known how engineering students' moral disengagement changes over the course of their college studies. In this paper, we conducted a longitudinal, mixed-methods study to investigate moral disengagement among undergraduate engineering students (n = 274) using Bandura's theory of moral disengagement as a theoretical framework. We found engineering students' overall propensity to morally disengage did not change over time, but there were statistically significant differences in student responses to three mechanisms of moral disengagement. We further investigated these findings with students' interviews. Based on our results, we discuss various theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Recent research on rater effects in performance assessments has increasingly focused on rater centrality, the tendency to assign scores clustering around the rating scale's middle categories. In the present paper, we adopted Jin and Wang's (2018) extended facets modeling approach and constructed a centrality continuum, ranging from raters exhibiting strong central tendencies to raters exhibiting strong tendencies in the opposite direction (extremity). In two simulation studies, we examined three model-based centrality detection indices (rater infit statistics, residual–expected correlations, and rater threshold SDs) as well as the raw-score SD in terms of their efficiency of reconstructing the true rater centrality rank ordering. Findings confirmed the superiority of the residual–expected correlation, rater threshold SD, and raw-score SD statistics, particularly when the examinee sample size was large and the number of scoring criteria was high. By contrast, the infit statistic results were much less consistent and, under conditions of large differences between criterion difficulties, suggested erroneous conclusions about raters' central tendencies. Analyzing real rating data from a large-scale speaking performance assessment confirmed that infit statistics are unsuitable for identifying raters' central tendencies. The discussion focuses on detecting centrality effects under different facets models and the indices' implications for rater monitoring and fair performance assessment. [ABSTRACT FROM AUTHOR]

This paper describes the phonological system of a monolingual Kuwaiti Arabic-speaking 9-year-old girl with Down Syndrome (DS) as part of a special crosslinguistic issue presenting individual profiles of children with protracted phonological development within the framework of constraints-based nonlinear phonology. Her responses to a 100-word speech test were audio-recorded and transcribed narrowly by two native speakers. Analyses showed low accuracy for word shapes (CV sequences), primarily because of expected deletion patterns in initial weak syllables and clusters, but also reflecting inaccuracies in segment length. Vowel match was also relatively low. For consonants, she unexpectedly showed lower accuracy for stops than typically later-developing liquids and fricatives. This case study provides researchers and speech-language pathologists with broader information about expected and unexpected patterns in children with DS and protracted phonological development in general. [ABSTRACT FROM AUTHOR]

Objective:To determine whether people’s beliefs about their illness, conceptualised by the common sense model (CSM), can prospectively predict adherence to self-management behaviours (including, attendance, medication, diet and exercise) in adults with acute and chronic physical illnesses. Design and Main Outcome Measures:Electronic databases were searched in September 2014, for papers specifying the use of the ‘CSM’ in relation to ‘self-management’, ‘rehabilitation’ and ‘adherence’ in the context of physical illness. Six hundred abstracts emerged. Data from 52 relevant studies were extracted. Twenty-one studies were meta-analysed, using correlation coefficients in random effects models. The remainder were descriptively synthesised. Results:The effect sizes for individual illness belief domains and adherence to self-management behaviours ranged from .04 to .13, indicating very weak, predictive relationships. Further analysis revealed that predictive relationships did not differ by the: type of self-management behaviour; acute or chronic illness; or duration of follow-up. Conclusion:Individual illness belief domains, outlined by the CSM, did not predict adherence to self-management behaviours in adults with physical illnesses. Prospective relationships, controlling for past behaviour, also did not emerge. Other factors, including patients’ treatment beliefs and inter-relationships between individual illness beliefs domains, may have influenced potential associations with adherence to self-management behaviours. [ABSTRACT FROM PUBLISHER]

Methods of uncertainty analysis are being included increasingly in regulatory chemical risk assessment. Although best practices have been established by several safety agencies in Europe and the United States, they exist only in the grey literature – there has been no comprehensive analysis of the scientific, peer-reviewed literature on these methods. We therefore conducted a systematic review of the recent peer-reviewed literature (2007–2013) on uncertainty analysis relevant to chemical risks. The main objective was to determine whether current methods are robust enough for regulatory use, because the methods used to protect public health must meet the most stringent scientific standards. Based on 297 papers, we concluded that the peer-reviewed literature is much more critical about the disadvantages of those methods, compared to the grey literature. Furthermore, uncertainty analyses can be influenced significantly by subjective expert judgment. As a suggested improvement, we developed guidelines for transparent reporting of uncertainty assessment results. [ABSTRACT FROM PUBLISHER]

In this paper, we consider several statistics on t-compositions. We exhibit a bijection between the set of t-compositions and a set of bargraphs, introduced in this paper, named t-bargraphs. As our main statistic is per – the perimeter of a given t-bargraph, we obtain the corresponding generating function. We find both an explicit and an asymptotic formula for the total length of the perimeter over all t-bargraphs with n-cells. [ABSTRACT FROM AUTHOR]

Objective: There is a paucity of quantitative measures of resilience specifically validated for young Aboriginal people in Australia. We undertook the first investigation of validity and reliability of the Connor-Davidson Resilience Scale (CD-RISC) in a sample of Australian Aboriginal people, with a focus on youth. Method: We conducted a cross-sectional study of resilience among a sample of 122 Aboriginal youth (15–25 years old) in New South Wales and Western Australia, featuring self-completes of the 10-item CD-RISC in online (N = 22) and face-to-face (N = 100) settings. A Rasch analysis using the 122 CD-RISC responses determined item independence, response category adequacy, differential item functioning, unidimensional measurement, person and item reliability, and item fit. Confirmatory factor analysis was also conducted, complementary to the Rasch analysis. Results: Four problematic items from the original instrument were removed, due to item dependence (items 2, 6 and 9; Q3,* > 0.30) and differential item functioning (item 4; > 0.43 logits between males and females). The final 6-item instrument exhibited improved item separation (ISI = 2.14) and reliability index values (IRI =.82) – suggesting an improved structure – however several limitations such as a prominent ceiling effect were evident (i.e., positive measure targeting coefficient of 0.99 logits). Conclusion: Findings suggest the CD-RISC instrument should be applied in Aboriginal contexts with caution. Further psychometric examination of the CD-RISC with Aboriginal youth is warranted before it can be used with confidence by researchers and clinicians. KEY POINTS What is already known about this topic: Resilience is generally thought of as positive outcomes despite exposure to risk. This can be a particularly important concept to consider in the period of youth and adolescence, when young people are experiencing wide ranging physical, emotional, and social changes and challenges. Aboriginal youth face unique circumstances that are necessary to consider when considering resilience relevant to an Aboriginal perspective. There is currently a lack in the literature in regards to defining and conceptualising resilience from an Aboriginal perspective, particularly relevant to young people. There is a dearth of instruments available that have been rigorously examined for their appropriateness and psychometric properties relating to resilience in Aboriginal youth. What this paper adds: This paper provides not only a first investigation of this version of the CD-RISC using Rasch analysis, but also the first time the CD-RISC's validity and reliability has been assessed for an Aboriginal sample in Australia. Analyses results illustrated a ceiling effect, highlighting the fact that for the instrument to be accessing the full range of resilience in the sample, new items need to be developed to tap into higher levels of resilience. With the findings of this paper as a foundation, further investigation and adaptation of the CD-RISC could potentially lead to a useful screening tool for assessing resilience and identifying Aboriginal youth who may require further support. [ABSTRACT FROM AUTHOR]

First, I thank Dr. Jensen for a paper that provides a great overview of the various disciplines that involve analysis of data, and which stimulated much discussion at the 2019 Stu Hunter conference. Because modeling and analysis is almost always an iterative process, version control systems are useful for managing analytics workflows, even beyond the Statistical or Machine Learning Engineering domains, and are commonly used by many industry analytics teams. Extensions to the commonly used version-control system git, such as git-annex ([4]) and Data Version Control (DVC [1]) (Open-source version control system) have been developed to try and address these issues. [Extracted from the article]

This paper explores the effect of regional innovation elements on innovation performance from the perspective of configurations. Based on the theory of innovation value chain, this paper divides the innovation process into two stages – technology development and technology commercialisation and proposes the realisation process model of regional innovation performance. Using the statistical data of province-level innovation systems in China, this study adopts a fuzzy-set qualitative comparative analysis to explore which combination of innovation elements can achieve high regional innovation performance and determines the difference between the stage of technology development and technology commercialisation. Results of the study can help regional policymakers to determine the most appropriate path to achieve high innovation performance according to the existing innovation elements in the regions. [ABSTRACT FROM AUTHOR]

This research explores the design, implementation, and evaluation of a prototype augmented reality application that assists operators in performing procedural tasks in control room settings. Our prototype uses a tablet display to supplement an operator's natural view of existing control panel elements with sequences of interactive visual and attention guiding cues. An experiment, conducted using a nuclear power plant simulator, examined university students completing both standard and emergency operating procedures. The augmented reality condition was compared against two other conditions – a paper-based procedure condition using paper manuals and a computer-based procedure condition using digital procedures presented on a desktop display. The results demonstrated that the augmented reality -based procedure system had benefits in terms of reduced mental workload in comparison to the other two conditions. Regarding task completion time, accuracy, and situation awareness, the augmented reality condition had no significant difference when compared against the computer-based procedure condition but performed better than the paper-based procedure condition. It was also found that the augmented reality condition resulted in fewer intra-team inquiry communication exchanges in comparison to both paper-based and computer-based conditions. The augmented reality condition, however, yielded poorer memory retention score when assessed against the other two conditions. [ABSTRACT FROM AUTHOR]

Discrete data are collected in many application areas and are often characterised by highly-skewed distributions. An example of this, which is considered in this paper, is the number of visits to a specialist, often taken as a measure of demand in healthcare. A discrete Weibull regression model was recently proposed for regression problems with a discrete response and it was shown to possess desirable properties. In this paper, we propose the first Bayesian implementation of this model. We consider a general parametrization, where both parameters of the discrete Weibull distribution can be conditioned on the predictors, and show theoretically how, under a uniform non-informative prior, the posterior distribution is proper with finite moments. In addition, we consider closely the case of Laplace priors for parameter shrinkage and variable selection. Parameter estimates and their credible intervals can be readily calculated from their full posterior distribution. A simulation study and the analysis of four real datasets of medical records show promises for the wide applicability of this approach to the analysis of count data. The method is implemented in the R package BDWreg. [ABSTRACT FROM AUTHOR]

Adaptive designs for multi-armed clinical trials have become increasingly popular recently because of their potential to shorten development times and to increase patient response. However, developing response-adaptive designs that offer patient-benefit while ensuring the resulting trial provides a statistically rigorous and unbiased comparison of the different treatments included is highly challenging. In this paper, the theory of Multi-Armed Bandit Problems is used to define near optimal adaptive designs in the context of a clinical trial with a normally distributed endpoint with known variance. We report the operating characteristics (type I error, power, bias) and patient-benefit of these approaches and alternative designs using simulation studies based on an ongoing trial. These results are then compared to those recently published in the context of Bernoulli endpoints. Many limitations and advantages are similar in both cases but there are also important differences, specially with respect to type I error control. This paper proposes a simulation-based testing procedure to correct for the observed type I error inflation that bandit-based and adaptive rules can induce. [ABSTRACT FROM AUTHOR]