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The Bergen–Yale Sexual Addiction Scale (BYSAS; [1]) is arguably the most popular questionnaire at present for assessing sex addiction. Employing Confirmatory Factor Analysis (CFA) and treating item scores as ordered categorical, we applied Weighted Least Square Mean and Variance Adjusted Chi-Square (WLSMV) extraction to investigate the longitudinal measurement and structural invariance of ratings on the BYSAS among 276 adults (mean = 31.86 years; SD = 9.94 years; 71% male) over a two-year period, with ratings at three yearly intervals. Overall, there was support for configural invariance, full loading, full threshold, the full unique factor invariance; and all structural (latent variances and covariances) components. Additionally, there was no difference in latent mean scores across the three-time points. The psychometric and practical implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

Intensive longitudinal (IL) data are increasingly prevalent in psychological science, coinciding with technological advancements that make it simple to deploy study designs such as daily diary and ecological momentary assessments. IL data are characterized by a rapid rate of data collection (1+ collections per day), over a period of time, allowing for the capture of the dynamics that underlie psychological and behavioral processes. One powerful framework for analyzing IL data is state-space modeling, where observed variables are considered measurements for underlying states (i.e., latent variables) that change together over time. However, state-space modeling has typically relied on continuous measurements, whereas psychological data often come in the form of ordinal measurements such as Likert scale items. In this manuscript, we develop a general estimation approach for state-space models with ordinal measurements, specifically focusing on a graded response model for Likert scale items. We evaluate the performance of our model and estimator against that of the commonly used "linear approximation" model, which treats ordinal measurements as though they are continuous. We find that our model resulted in unbiased estimates of the state dynamics, while the linear approximation resulted in strongly biased estimates of the state dynamics. Finally, we develop an approximate standard error, termed slice standard errors and show that these approximate standard errors are more liberal than true standard errors (i.e., smaller) at a consistent bias. [ABSTRACT FROM AUTHOR]

Joint modeling of longitudinal and survival data is increasingly used in biomedical studies. However, existing joint models are not applicable to model the longitudinal ordinal responses with non-ignorable missing values caused by the occurrence of events in a multi-state process. In this article, we introduce a joint model for longitudinal ordinal measurements and multi-state data. Our proposed joint model consists of two sub-models: a proportional odds sub-model for longitudinal ordinal measurements and a multi-state sub-model with transition-specific proportional hazards for times of transitions between different health states, both linked by shared random effects. The model parameters were estimated employing the maximum likelihood method for a piecewise constant baseline hazard function. The proposed joint model is evaluated in a simulation study and, as an illustration, it is fitted to real data from people with human immunodeficiency virus. [ABSTRACT FROM AUTHOR]

In many medical studies, questionnaires or instruments with item ratings are often used to measure the health outcomes reflecting the disease status. Therefore, combining these item ratings to derive a score that reflects the disease status is an important issue. This paper proposes a new weighted method with the weights determined by maximizing the broad sense agreement Peng et al. [L. Peng, R. Li, Y. Guo, and A. Manatunga, A framework for assessing broad sense agreement between ordinal and continuous measurements, J. Am. Stat. Assoc. 106 (2011), pp. 1592–1601.] between the new score and the disease status measured by an ordinal scale. Theoretical and simulation results demonstrate the validity of our proposed optimal weights. We illustrate our method via an application to a post-traumatic stress disorder (PTSD) study. [ABSTRACT FROM AUTHOR]

The functionalist approach claims that autobiographical memory functions could be part of narrative identity. If so, the use of memory functions in personal narratives should be as stable as other properties of narrative identity. Testing this claim, the present study elicited repeated narratives and functional self-ratings for turning point and low point memories from 145 undergraduates (68.90 % female) in a two-wave eight-month longitudinal study. Stability of memory functions in specific memories was conceptualized in terms of mean-level and rank-order stability. Results showed little mean-level stability, yet substantial rank-order stability for memory functions regardless of assessment. The later use of the same memory functions in repeated narratives was predicted by baseline of functions at T1, age of event, valence, and frequency of rehearsal. Combining these results with theories on autobiographical memory and narrative identity suggests that memory functions might be a stable property of narrative identity hitherto overlooked. [ABSTRACT FROM AUTHOR]

Background Desirability of outcome ranking (DOOR) is an emerging approach to clinical trial outcome measurement using an ordinal scale to incorporate efficacy and safety endpoints. Methods We applied a previously validated DOOR endpoint to a cohort of CAMERA2 trial participants with methicillin-resistant Staphylococcus aureus bacteremia (MRSAB). Participants were randomly assigned to standard therapy, or to standard therapy plus an antistaphylococcal β-lactam (combination therapy). Each participant was assigned a DOOR category, within which they were further ranked according to their hospital length of stay (LOS) and duration of intravenous antibiotic treatment. We calculated the probability and the generalized odds ratio of participants receiving combination therapy having worse outcomes than those receiving standard therapy. Results Participants assigned combination therapy had a 54.5% (95% confidence interval [CI], 48.9%–60.1%; P =.11) probability and a 1.2-fold odds (95% CI,.95–1.50; P =.12) of having a worse outcome than participants on standard therapy. When further ranked according to LOS and duration of antibiotic treatment, participants in the combination group had a 55.6% (95% CI, 49.5%–61.7%) and 55.3% (95% CI, 49.2%–61.4%) probability of having a worse outcome than participants in the standard treatment group, respectively. Conclusions When considering both efficacy and safety, treatment of MRSAB with a combination of standard therapy and a β-lactam likely results in a worse clinical outcome than standard therapy. However, a small benefit of combination therapy cannot be excluded. Most likely the toxicity of combination therapy outweighed any benefit from faster clearance of bacteremia. [ABSTRACT FROM AUTHOR]

Objective: Dimensional variable weighting is required to calculate the composite index of policing activities in mining and quarrying activities. The purpose of weighting is to determine the Ranking and priority of each indicator and dimension, considering that each indicator does not necessarily have the same value in the actual situation. The weighting method used in this study uses a subjective method using expert opinion. Method: The Ranking carried out by experts is then calculated using rank order centroids. The results of this weighting show that expert opinion can be used to aggregate weights with specific values that can be used as weights for each dimension. Conclusion: The results of this study show that weighting by Ranking by experts through subjective methods can be used to compile rankings or weights of variables for index preparation. [ABSTRACT FROM AUTHOR]

This research explored social work licensure board members' decision-making about alleged violations by social workers and subsequent sanctioning. Participants served within the last five years on a jurisdictional board regulating social workers in the US. The survey included factors related to board member decision-making, rank ordering the seriousness of listed allegations, and four vignettes where participants rated the seriousness of the allegations and the importance for a board to discipline the social worker. Persons serving on twelve US boards that license social workers (n=21) read four vignettes of hypothetical social worker violations and rated the seriousness of the violations and the importance of disciplining the social workers. The violations, in order from most (7) to least severe (1) were fraudulent record keeping (5.63), professional boundaries (non-sexual) (5.37), impairment (5.1), and improper termination (2.63). The importance to discipline, in order from most (7) to least important (1), were: professional boundaries (non-sexual) (6.1), fraudulent reporting (5.68), impairment (4.4), and improper termination (2.47). Having an MSW degree, as opposed to BSW, was the only variable increasing the seriousness of the offense in all four vignettes. Results may help with understanding how licensing boards review alleged violations and determine sanctions. [ABSTRACT FROM AUTHOR]

The purpose of the research was to analyze how conflict management is in Basic Education schools located in the Province of El Oro, Ecuador. It was theoretically based on the authors Pérez (2020), Eguiguren (2021), Ahumada-Méndez (2019) and Carbonero (2018) among others. The research was framed within the descriptive positivist approach with a field, non-experimental and transectional design. The population was made up of managers and teachers, assumed as a population census. To collect the information, a scale-type questionnaire was designed as an instrument, with an ordinal level of measurement. The instrument was validated through experttested content validity using the Rank Proportion Coefficient method, yielding a CPR value of 0.89, indicating that it has good validity and agreement to be applied. Reliability is calculated through Cronbach's alpha coefficient, whose value was 0.743, indicating that the instrument has a high reliability. Descriptive statistics were used as a data processing and analysis technique, through the calculation of frequency distribution and arithmetic means. The results highlighted that there are discrepancies between the opinions of managers and teachers regarding the way in which the former handle conflicts, with managers stating that the strategies are present, while teachers believe that they are absent. It is recommended to identify the type of conflict and its differences in order to be able to identify and apply the most efficient model for its approach and management. [ABSTRACT FROM AUTHOR]

Objective: Accumulated evidence indicates both stable and malleable parts of inter‐individual differences in the broad Big Five domains. Less is known, however, about stability and change at the more diversified facet level. With the current study, we fill this gap by investigating personality stability and change across midlife and old age. Method: We apply local structural equation measurement models and second‐order growth curve models to four waves of data obtained with the full NEO Personality Inventory (NEO‐PI‐R) collected over 11 years from 1667 adults (Mage = 62.69 years, SDage = 15.62, 55% female) who participated in the Seattle Longitudinal Study. Results: Measurement invariance analyses indicated that the psychometric properties of the NEO‐PI‐R facets are comparable across time and age. Results revealed substantial rank‐order stabilities across all facets, yet the exact pattern varied strongly between facets of the same trait and across traits. Mean‐level change of facets from midlife to old age largely mirrored the mean‐level change observed for the broader traits. Conclusion: We discuss conceptual implications and argue that in the face of overall stability across midlife and old age, changes in the rank‐ordering of people reveals a much more complex and diverse pattern of development than analyses at the trait level suggest. [ABSTRACT FROM AUTHOR]

The authors propose a new conceptual basis for predicting when and why consumers match others' consumption choices. Specifically, they distinguish between ordinal ("ranked") versus nominal ("unranked") attributes and propose that consumers are more likely to match others on ordinal than on nominal attributes. Eleven studies involving a range of different ways of operationalizing ordinal versus nominal attributes collectively support this hypothesis. The authors' conceptualization helps resolve divergent findings in prior literature and provides guidance to managers on how to leverage information about prior customers' choices and employees' recommendations to shape and predict future customers' choices. Furthermore, the authors find process evidence that this effect is driven in part by consumers' beliefs that a failure to match on ordinal (but not nominal) attributes will lead to social discomfort for one or both parties. Although the primary focus is on food choices, the effects are also demonstrated in other domains, extending the generalizability of the findings and implications for managerial practice and theory. Finally, the conceptual framework offers additional paths for future research. [ABSTRACT FROM AUTHOR]

This article proposes a new approach to the measurement of intergenerational mobility in education. Borrowing the concept of inequality‐sensitive and additive achievement measure axiomatically developed by Apouey et al., we derive new indices of upward, downward, and total mobility, using a "movement approach." It turns out that the Prais‐Bibby and Bartholomew mobility indices are particular cases of the mobility indices we introduce. We then present an empirical illustration based on the 2016 European Social Survey. Particular attention is given to within country differences between fathers to children and mothers to children educational mobility. When comparing two countries, we also make a distinction between gross and net mobility, the latter referring to the case where country differences in the educational structure of parents and children are neutralized. [ABSTRACT FROM AUTHOR]

In the literature on numerical cognition, the presence of the capacity to distinguish between numerosities by attending to the number of items, rather than continuous properties of stimuli that correlate with it, is commonly taken as sufficient indication of numerical abilities in cognitive agents. However, this literature does not take into account that there are non-numerical methods of assessing numerosity, which opens up the possibility that cognitive agents lacking numerical abilities may still be able to represent numerosity. In this paper, I distinguish between numerical and non-numerical methods of assessing numerosity and show that the most common models of the internal mechanisms of the so-called number sense rely on non-numerical methods, despite the claims of their proponents to the contrary. I conclude that, even if it is established that agents attend to numerosity, rather than continuous properties of stimuli correlated with it, an answer to the question of the existence of the number sense is still pending the investigation of a further issue, namely, whether the mechanisms the brain uses to assess numerosity qualify as numerical or nonnumerical. [ABSTRACT FROM AUTHOR]

Children’s knowledge of the ordinal relations among number symbols is related to their mathematical learning. Ordinal knowledge has been measured using judgment (i.e., decide whether a sequence of three digits is in order) and ordering tasks (i.e., order three digits from smallest to largest). However, the question remains whether performance on these two ordinal tasks tap into similar cognitive processes. Canadian children (N = 87; Age M = 8.7 years, Grade 3) completed symbolic number tasks (i.e., number comparison, ordering, and order judgment) and measures of arithmetic fluency (i.e., addition and subtraction) and working memory (i.e., digit span backward). For both ordinal tasks, there was a reverse distance effect for ordered sequences such that children responded faster to adjacent than to non-adjacent sequences (e.g., 2 3 4 vs. 4 7 9) and a canonical distance effect for unordered sequences such that children responded faster to non-adjacent than to adjacent sequences (e.g., 4 2 3 vs. 4 9 7). Working memory and number comparison each predicted unique variance in the ordinal measures (ordering, order judgment, and a latent ordinal factor based on the two measures). Furthermore, ordinal skills superseded the role of number comparison as the key predictor of arithmetic, controlling for children’s gender and working memory skills. In summary, although both ordering and order judgment tasks index ordinal knowledge, a latent factor that excludes task-specific error may be a better index than either task separately. [ABSTRACT FROM AUTHOR]

We explore the inequality measurement of a discrete ordinal variable between social groups. We provide an axiomatic characterization for the Net Difference Index (Lieberson: Sociol. Methodol. 7, 276–291 1976), that makes use of rank-domination to evaluate the discrepancy between the distributions of two social groups over ordered categories. Adapting well-known principles of cardinal inequality measurement to the between-group ordinal inequality setting, we show that the Net Difference Index mimics the Gini Index in terms of its relationship to the Lorenz curve, in our setting. [ABSTRACT FROM AUTHOR]

Background: The Rasch model allows for linear measurement based on ordinal item responses from rating scales commonly used to assess health outcomes. Such linear measures may be inconvenient since they are expressed as log-odds units (logits) that differ from scores that users may be familiar with. It can therefore be desirable to transform logits into more user-friendly ranges that preserve their linear properties. In addition to user-defined ranges, three general transformations have been described in the literature: the least measurable difference (LMD), the standard error of measurement (SEM) and the least significant difference (LSD). The LMD represents the smallest possible meaningful unit, SEM relates the transformed scale values to measurement uncertainty (one unit on the transformed scale represents roughly one standard error), and LSD represents a lower bound for how coarse the transformed scale can be without loss of valid information. However, while logit transformations are relatively common in the health sciences, use of LMD, SEM and LSD transformations appear to be uncommon despite their potential role. Methods: Logit transformations were empirically illustrated based on 1053 responses to the Epworth Sleepiness Scale. Logit measures were transformed according to the LMD, SEM and LSD, and into 0–10, 0-100, and the original raw score (0–24) ranges. These transformations were conducted using a freely available Excel tool, developed by the authors, that transforms logits into user-defined ranges along with the LMD, SEM and LSD transformations. Results: Resulting LMD, SEM and LSD transformations ranged 0-34, 0-17 and 0-12, respectively. When considering these relative to the three user-defined ranges, it is seen that the 0-10 range is narrower than the LSD range (i.e., loss of valid information), and a 0-100 range gives the impression of better precision than there is, since it is considerably wider than the LMD range. However, the 0-24 transformation appears reasonable since it is wider than the LSD, but narrower than the LMD ranges. Conclusions: It is suggested that LMD, SEM and LSD transformations are valuable for benchmarking in deciding appropriate ranges when transforming logit measures. This process can be aided by the Excel tool presented and illustrated in this paper. [ABSTRACT FROM AUTHOR]

In general, when the assumption of normality, heteroscedasticity and independency are not satisfied by the experimental data, we prefer nonparametric methods to analyse the data. Friedmann (1937) proposed a non-parametric test for testing the significance of means of several treatments. In this paper, an attempt is made to modify Friedman test statistic for testing the data when the experiment is conducted in a Randomized block design layout and the measurements are in ordinal scale and compared with Friedman test statistic. [ABSTRACT FROM AUTHOR]

Enjoying a cup of coffee is one of the hobbies of most people in Indonesia in various circles, both young and old. However, since the Covid-19 outbreak, the government has asked the public to reduce activities outside the home. Lucky's Koffiee is feeling the impact of this epidemic. Experiencing a decrease in revenue and the amount of raw material remaining is an important concern for management. Using Rank Order Centroid (ROC) for weighting criteria and a decision support system using the Simple Additive Weighting (SAW) method as consideration for selecting suppliers of raw materials that are in accordance with the conditions of the Covid-19 pandemic by using the criteria of price, quality, service, and timeliness as consideration variables. [ABSTRACT FROM AUTHOR]

A popular framework of the supplier selection process is usually characterized by problem definition, criteria formulation, supplier screening, and supplier selection. The literature review suggested limitations of this framework as it ignores the screening of criteria (beyond criteria weighing) and evaluators (buyers) and its inability to guide the supplier selection problems where a measure of confidence or trust is needed to confirm the reliability of the selected supplier. While extending de Boer's influential supplier selection framework, the current study argues that the supplier selection problem is not merely about ranking suppliers based on given criteria; instead, it involves evaluating criteria and evaluators as well. Guided by the theory of statistics and the Ordinal Priority Approach (OPA), the study pioneers a probabilistic approach of supplier evaluation and selection under incomplete information using a novel Confidence Level measure. The study suggests, the probability that a supplier shortlisted for selection is actually the optimum choice or not can be explained through a probability distribution, called W-distribution, therefore, confidently preventing the decision-makers from selecting the sub-optimum suppliers. The study presents a novel contribution to the theory of multiple-attribute decision-making through the OPA. The proposed approach can help build intelligent decision support systems to aid managers while providing them with early warning tools and suggestions to improve confidence in their selection. [ABSTRACT FROM AUTHOR]

The occurrence of major life events is associated with changes in well-being and personality. To better understand these effects, it is important to consider how individuals perceive major life events. Although theories such as appraisal theory and affective adaptation theory suggest that event perceptions change over time and that these changes are relevant for personality and well-being, stability and change of perceived event characteristics have not been systematically examined. This article aims to fill this gap using data from a longitudinal study (N = 619 at T1). In this study, participants rated nine perceived characteristics of the same major life event up to five times within 1 year. We estimated rank-order and mean-level stabilities as well as intraclass correlations of these life event characteristics with continuous time models. Furthermore, we computed continuous time models for the stability of affective well-being and the Big Five personality traits to generate benchmarks for the interpretation of the stability of the life event characteristics. Rank-order stabilities for the life event characteristics were lower than for the Big Five, but higher than for affective well-being. Most of the variance in life event characteristics was explained by between-person differences. Furthermore, we found a significant mean-level increase for the life event characteristic change in world views and a significant decrease for extraordinariness. These mean-level changes are in line with the meaning-making literature and affective adaptation theory, whereas the rather high rank-order stability of the life event characteristics challenges the importance of reappraisal processes of major life events. [ABSTRACT FROM AUTHOR]

Several studies have suggested that the rank-order stability of personality increases until midlife and declines later in old age. However, this inverted U-shaped pattern has not consistently emerged in previous research; in particular, a recent investigation implementing several methodological advances failed to support it. To resolve the matter, we analyzed data from two representative panel studies and investigated how certain methodological decisions affect conclusions regarding the age trajectories of stability. The data came from Australia (N = 15,465; Study 1) and Germany (N = 21,777; Study 2), and each study included four waves of personality assessment. We investigated the life span development of the rank-order stability of the Big Five for 4-, 8-, and 12-year intervals. Whereas Study 1 provided strong evidence for an inverted U-shape with rank-order stability declining past age 50, Study 2 provided more mixed results that nonetheless generally supported the inverted U-shape. This developmental trend held for single personality traits as well as for the overall pattern across traits; and it held for all three retest intervals—both descriptively and in formal tests. Additionally, we found evidence that health-related changes accounted for the decline in rank-order stability in older age. This suggests that if analyses are implicitly conditioned on health (e.g., by excluding participants with missing data on later waves), the decline in stability in old age will be underestimated or even missed. Our results provide further evidence for the inverted U-shaped age pattern in personality stability development but also extend knowledge about the underlying processes. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) methods are becoming widespread, especially when data are not sufficient to build classical statistical models, as is the case for cyber risk management. However, when applied to regulated industries, such as energy, finance, and health, AI methods lack explainability. Authorities aimed at validating machine learning models in regulated fields will not consider black‐box models, unless they are supplemented with further methods that explain why certain predictions have been obtained, and which are the variables that mostly concur to such predictions. Recently, Shapley values have been introduced for this purpose: They are model agnostic, and powerful, but are not normalized and, therefore, cannot become a standardized procedure. In this paper, we provide an explainable AI model that embeds Shapley values with a statistical normalization, based on Lorenz Zonoids, particularly suited for ordinal measurement variables that can be obtained to assess cyber risk. [ABSTRACT FROM AUTHOR]

I study yearly changes in personal well-being combining data on current, retrospective and prospective life satisfaction from the German Socio-Economic Panel. Predicted and remembered changes in life satisfaction are both positive on average and match well, whereas the average year to year-change inferred from reports of current life satisfaction is negative. Retrospective assessments of past well-being are strongly influenced by current life satisfaction, significantly related to past life satisfaction and linked to past predictions of current satisfaction. Due to different problems related to the ordinal measurement scale, changes in subjective reference systems and recall ability, the analysis overall suggests that direct reports of intertemporal changes provide valuable additional information for the analysis of individual well-being. [ABSTRACT FROM AUTHOR]

The maturity ogive is vital to defining the fraction of a population capable of reproduction. In this study, we proposed a novel approach, a Bayesian multilevel ordinal regression (i.e., Bayesian continuation ratio model), to model the maturity ogive. The model assumes that the observed maturity stage originates from the categorization of latent continuous variables. We demonstrated this approach by testing whether there are differences in the maturity ogive of skipjack tuna (Katsuonus pelamis) in the western and central Pacific Ocean between two school types, i.e., free-swimming and floating-object-associated schools. The model results show that K. pelamis, given the same fork length, are more likely to have a higher maturity stage in a free-swimming school than those associated with floating objects. The gonadosomatic index revealed the same conclusion. Our results indicate that fish aggregation devices (FADs) could negatively affect the maturity of K. pelamis and consequently reduce the population reproductive potential. This study provides (1) an alternative approach to analyze fisheries ordinal data; (2) important quantitative evidence to evaluate the existing ecological hypotheses; and (3) implications for tuna fisheries management.

Access to higher education by the general populace in South Africa has been steadily increasing over the last decade. With this increase in access, major challenges have presented themselves that may compromise the transformational agenda for higher education in South Africa. The focus of this research was to examine the challenges associated with student accommodation. In total, 600 questionnaires were dispatched to students from the five campuses of University of KwaZulu-Natal and 453 were returned which gave a 75.5% response rate. The research instrument consisted of 31 items, with a level of measurement at a nominal or an ordinal level. Data obtained from the respondents included biographical data, quality of accommodation, accessibility and adequacy of accommodation, security, safety and health issues in the University accommodation. The questionnaire was the primary tool that was used to collect data and was distributed to students who lived in residences at the University of KwaZulu-Natal (UKZN). The data collected from the responses were analysed with SPSS version 24.0. The study's focus was to examine various challenges associated with student accommodation in South Africa specifically UKZN and results indicated that accessibility to the university accommodation for residential purposes is a great challenge for many students. Other issues faced by students include insecurity on campus, irregular security checks, inefficient and untimely manner of the quality of services rendered by the hall management. Good and efficient accommodative measures by the university are necessary for quality academic output; hence, the need for critical intervention, as suggested in the study. [ABSTRACT FROM AUTHOR]

This paper explores the use of social media specifically WhatsApp for learning by undergraduate students of Arts and Science Colleges. Literature review shows that social media could be used as an instrument for learning in different parts of the world and reflects the advantages and disadvantages of using social media for learning. This paper uses Communities of Inquiry (CoI) model to prove the point that production of knowledge is done through three presences explained by the conceptual model of CoI developed by researcher. Survey questionnaire is used to elicit answers from the undergraduate students. 769 samples from 10 select Arts and Science colleges in Krishna District, Andhra Pradesh, South India, were collected. Nominal and ordinal measurements are used to construct the survey questionnaire. Demographic results presented in this paper show cross-sectional representation of the population. Using results of crosstabulation and Kruskal-Wallis-H tests, 3 sets of significant statements concerning teaching, social and cognitive and learning presences are tested and the results are presented. The paper concludes that results of tests prove that social presence and cognitive and learning presence are reflected more than the teaching presence. The social, cognitive, and learning presences make teaching presence a reality. [ABSTRACT FROM AUTHOR]

Assessing the environmental (un)sustainability of products appears to be a complex task for consumers, and despite the growing number of eco-information schemes, their effectiveness leaves room for improvement. Eco-ratings (e.g., https://www.ecoratingdevices.com/ratings/) quantify the environmental (un)sustainability of products in a given choice set or assortment in a standardized way, using a predefined score range (e.g., from 1 to 5) with ordinal or interval measurement level. Since eco-ratings do not have a one-to-one relation to a quantifiable physical reality (e.g., CO2 emissions), their framing direction is essentially arbitrary: in a five-point eco-rating one could frame the scores positively (e.g., 1 = not environmentally friendly, 5 = very environmentally friendly) or negatively (e.g., 1 = very damaging for the environment, 5 = not damaging for the environment). Based on three experiments, we find that negative (vs. positive) framing of eco-ratings increases the choice likelihood of the most ecological option from a choice set (Study 1). Moreover, eco-ratings positively affect anticipated pride, which in turn has a positive effect on purchase intention, and the effect of eco-ratings on pride is stronger when eco-ratings are negatively framed (studies 2a and 2b). In other words, emphasizing that a product is less damaging to the environment, rather than more environmentally friendly, relative to other products, increases the anticipation of pride and leads to stronger intentions to buy more environmentally sustainable products. Apart from the theoretical contributions, this paper has important practical implications for the communication of the environmental (un)sustainability of products. • Framing eco-ratings negatively (vs. positively) increase purchase intention of the most ecological option from a choice set. • Eco-ratings positively affect anticipated pride, which increases purchase intention. • The effect of eco-ratings on pride is stronger when eco-ratings are negatively (vs. positivey) framed. [ABSTRACT FROM AUTHOR]

• A self-organized mechanism based consensus framework is presented. • Non-cooperative behaviors are detected and managed at the element level of MAEMs. • A novel distance-based ordinal consensus measurement is proposed. • Simulation analysis is presented to show the effectiveness of our proposals. In consensus-based multi-attribute group decision making (MAGDM) problems, decision makers (DMs) may exhibit non-cooperative behaviors since they usually have different individual interests (sometimes conflicting) or limited knowledge, which strongly affects the efficiency of consensus and the quality of decision outcomes. Additionally, the existing MAGDM studies mainly focus on the cardinal consensus, and the ordinal consensus is ignored. Thus, this paper proposes a self-organized mechanism based framework to manage non-cooperative behaviors and ordinal consensus in MAGDM. First, a dual-membership function based on the basic idea of synergy theory is designed to detect non-cooperative behaviors at the element level of the multiple attribute evaluation matrix (MAEM), and then the weights of elements with non-cooperative behaviors are penalized automatically. In this way, the negative effects of non-cooperative behaviors can be eliminated. Next, a novel preference ranking-based ordinal consensus approach is proposed, which calculates an ordinal consensus based on the preference rankings of alternatives between individuals and the group. If the pre-defined consensus level is not reached, the feedback adjustment is used to help DMs modify their MAEMs to improve the consensus level; otherwise, the selection process is utilized to choose the optimal alternative(s). Finally, detailed simulation experiments and comparative analysis are designed to show the properties and effectiveness of the proposed framework, and an illustrative angel investment case is presented to demonstrate the calculation process and usability. [ABSTRACT FROM AUTHOR]

Common definitions of bullying, employed in research and public policy alike, are generally based on adult-imposed categories. To account for students' needs in school, research should aim to include their voices more often. However, a major challenge for educational research in general, and bullying research in particular, is finding methods that enable students to participate in the discussion. The aim of this small, exploratory and in-depth study was to further the understanding of bullying and provide insights by examining students' subjective viewpoints about bullying. Using Q methodology, a total of 29 Swedish 11- and 13-year-olds from one school were given a Q set, comprising 23 items to rank order. Aspects such as the characteristics, modes and types, as well as the context of bullying, were taken into account in the construction of the Q set. Through analysis it was possible to identify two distinct viewpoints, which were then qualitatively interpreted and described. The viewpoints which emerged within this small, exploratory analysis suggested some interesting distinctions and age-related emphases. Specifically, the older students tended to rank items taking place offline as more severe, compared with items describing bullying taking place online. Further, bullying in private settings was perceived as more severe amongst the younger students, while items describing repetitive bullying in public settings appeared to be of greatest importance when defining bullying behaviour amongst the older students. The relational types of bullying were not ranked as highly characteristic for bullying by younger or older students. Further research with larger data sets is necessary to investigate these emerging findings. The study draws attention to the need for adults to maintain a focus on students' behaviours offline, as well as online: in this highly digital age, it is easy for the offline context to be inadvertently overlooked. When it comes to younger students, anti-bullying efforts targeting bullying in private settings and acknowledging potential harm may be more suitable than anti-bullying efforts targeting stigma and shame, which may, in turn, better support the needs of older students. The study also shines a light on the importance of using participatory methodologies that allow students to express their own perspectives. [ABSTRACT FROM AUTHOR]

The regression model with ordinal outcome has been widely used in a lot of fields because of its significant effect. Moreover, predictors measured with error and multicollinearity are long-standing problems and often occur in regression analysis. However there are not many studies on dealing with measurement error models with generally ordinal response, even fewer when they suffer from multicollinearity. The purpose of this article is to estimate parameters of ordinal probit models with measurement error and multicollinearity. First, we propose to use regression calibration and refined regression calibration to estimate parameters in ordinal probit models with measurement error. Second, we develop new methods to obtain estimators of parameters in the presence of multicollinearity and measurement error in ordinal probit model. Furthermore we also extend all the methods to quadratic ordinal probit models and talk about the situation in ordinal logistic models. These estimators are consistent and asymptotically normally distributed under general conditions. They are easy to compute, perform well and are robust against the normality assumption for the predictor variables in our simulation studies. The proposed methods are applied to some real datasets. [ABSTRACT FROM AUTHOR]

In this paper, joint modeling of longitudinal ordinal measurements and time to some events of interest as competing risks is discussed. For this purpose, a latent variable sub-model under linear mixed-effects assumption is considered for modeling ordinal longitudinal measurements. Also, a Weibull cause-specific sub-model is used to model competing risks data. These two sub-models are simultaneously considered in a unique model by a shared parameter model framework. Some simulation studies are performed for illustration of the proposed approaches; also, the proposed approaches are used for analyzing 15 years of lipid and glucose follow-up study in Tehran. [ABSTRACT FROM AUTHOR]

Gender-nonconforming (GN) children are often perceived less positively, which may harm their well-being. We examined the development of such perceptions and an intervention to modify them. Chinese children's appraisals were assessed using multiple measures (verbal responses, sharing, and rank order task) after viewing vignettes of gender-conforming (GC) and GN hypothetical peers. In Study 1, children (N = 210; 4-, 5-, 8-, and 9-year-olds) were less positive toward GN than GC peers, especially if they were older or if the peers were boys. In Study 2 (N = 211, 8- and 9-year-olds), showing children exemplars of GN peers who displayed positive and GC characteristics subsequently reduced bias against gender nonconformity. These findings inform strategies aimed at reducing bias against gender nonconformity. [ABSTRACT FROM AUTHOR]

Questionnaire surveys often deal with items by which we would like to identify possible associations. These items/variables can be measured on the basis of nominal, ordinal or interval scale. This paper provides an overview of statistical measures of association between two ordinal variables that are used most commonly. It also offers a display of the outputs from the SPSS program, in addition to the description of correlation coefficient calculations. [ABSTRACT FROM AUTHOR]

The concept of broad sense agreement (BSA) has recently been proposed for studying the relationship between a continuous measurement and an ordinal measurement. They developed a nonparametric procedure for estimating the BSA index, which is only applicable to completely observed data. In this work, we consider the problem of evaluating BSA index when the continuous measurement is subject to censoring. We propose a nonparametric estimation method built upon a derivation of a new functional representation of the BSA index, which allows for accommodating censoring by plugging in the nonparametric survival function estimators. We establish the consistency and asymptotic normality for the proposed BSA estimator. We also investigate an alternative approach based on the strategy of multiple imputation, which is shown to have better empirical performance with small sample sizes than the plug-in method. Extensive simulation studies are conducted to evaluate our proposals. We illustrate our methods via an application to a Surgical Intensive Care Unit study. [ABSTRACT FROM AUTHOR]

The aim of the study covers, at first, the rank comparison drawn among mutual funds at categorical and investment policy level and secondly, among the selected three families of performance measures against famous Sharpe ratio. The Spearman rank order correlation and mean rank order approach have been used for this purpose. The major findings of the study reveal that the most of the performance measures have shown a similar ranking order of mutual funds, at the investment policy level, against the standard measure i.e., Sharpe ratio. However, funds that have shown a non-normal trend, led to misspecification syndrome. [ABSTRACT FROM AUTHOR]

The measurement scale of exam scores is ordinal. This ordinal measurement implies that monotonic transformations of published scales convey the same information. Hence, countries should not be ranked according to averaged scores because there may be transformations that would change the mean-based rankings. We suggest alternatives to the mean-based ranking procedure that yield informative and robust rankings. An implementation of these procedures, using PISA 2012 math scores, suggests that previous mean-based country rankings are sensitive to the aforementioned transformations. [ABSTRACT FROM AUTHOR]

This research examines the performance of the previously proposed cutoff values of alternative fit indices (i.e., change in comparative fit index [ ΔCFI ], change in Tucker–Lewis index [ ΔTLI ], and change in root mean squared error of approximation [ Δ RMSEA ]) to evaluate measurement invariance for exploratory structural equation modeling (ESEM) models with simulated data. It is important to revisit these cutoff values because they were used widely in validity studies utilizing ESEM models to evaluate measurement invariance for ordinal indicators, but in fact, these cutoff values were developed under confirmatory factor analysis models with continuous indicators. Results of this study show that different cutoff values of ΔCFI , ΔTLI , and Δ RMSEA should be used for ESEM models with ordinal indicators. Evaluation of partial invariance for ESEM models is also discussed. [ABSTRACT FROM AUTHOR]

The paper proposes a new methodology to measure cyber risks which, instead of using quantitative loss data, often not available, employs ordinal data. The method relies on the construction of a criticality index, whose properties are discussed and compared with alternative measures employed in operational risk measurement. The methodology is illustrated on data regarding cyber attacks collected at the worldwide level. The proposed measure is found to be quite effective to rank cyber risk types. Thus, from a policy perspective, it can be useful to guide the implementation of preventive actions. [ABSTRACT FROM AUTHOR]

Ordinal missing data are common in measurement equivalence/invariance (ME/I) testing studies. However, there is a lack of guidance on the appropriate method to deal with ordinal missing data in ME/I testing. Five methods may be used to deal with ordinal missing data in ME/I testing, including the continuous full information maximum likelihood estimation method (FIML), continuous robust FIML (rFIML), FIML with probit links (pFIML), FIML with logit links (lFIML), and mean and variance adjusted weight least squared estimation method combined with pairwise deletion (WLSMV_PD). The current study evaluates the relative performance of these methods in producing valid chi-square difference tests ( Δ χ 2 ) and accurate parameter estimates. The result suggests that all methods except for WLSMV_PD can reasonably control the type I error rates of Δ χ 2 tests and maintain sufficient power to detect noninvariance in most conditions. Only pFIML and lFIML yield accurate factor loading estimates and standard errors across all the conditions. Recommendations are provided to researchers based on the results. [ABSTRACT FROM AUTHOR]

• Barriers are classified for the purpose of safety management. • Management tasks for barriers are identified and modelled. • Delivery systems deliver suitable controls and resources to complete barriers. • The link between delivery systems and barriers is further developed. • The quantification of the competence delivery system helps developing the approach to safety management modelling. Safety Management Systems usually follow specified formats, as required by standards and other procedures. The quality of such systems is often obtained with assessments at the ordinal measurement level. This paper introduces a barrier-based safety management system coupled with a quantitative approach to safety management modelling. The risk management part of this system is composed of so-called delivery systems, which describe the management processes in place in order to manage barriers. The proposed approach aims to determine how the delivered management factors affect risks by influencing the functioning of barriers. Taking the competence delivery system as an example, competent people are delivered to carry out the tasks of barriers, and these tasks guarantee barriers' effectiveness. In this research, barriers are grouped into five types. By quantifying competence indicators and the performance of each type of barrier, the link between a delivery system (competence) and barriers is established. Other delivery systems can be quantified in a similar way, meaning that safety management systems will work more efficiently with such monitoring. In addition, this quantification can be used as input for audits, by making assessments more transparent. [ABSTRACT FROM AUTHOR]

Investigations of biosimilarity between reference drugs and test drugs required statistical tests; in addition, statistical tests to evaluate biosimilarity have been recently proposed. Ordinal outcome data has been observed in research; however, appropriate statistical tests to deal with ordinal endpoints for biosimilar have not yet been proposed. This paper extends existing design for ordinal endpoints. Using measure of nominal-ordinal association and relative distances between drugs are defined so that testing procedures are developed. Through simulation studies, we investigate type I error rate and power to show the performance of our suggested method. Furthermore, a comparison between the statistical tests and other designs is proviede to show significance of ordinal endpoints. [ABSTRACT FROM AUTHOR]

Consumers are increasingly saturated by market research, which leads to decreasing response rates and an increased danger of response bias. Market researchers thus face the challenge of recruiting respondents, increasing response rates and reducing respondent fatigue by making questionnaires as short and pleasant as possible. One way of achieving this is to replace traditionally used ordinal multi-category answer formats (such as Likert-type scales) with forced binary scales. This proposition k attractive only if it indeed shortens the survey lime while not compromising the quality of managerial insights from the data. This study investigates these conditions. Results from a repeat-measurement design indicate that managerial interpretations do not differ substantially between [he two answer formats, responses are equally reliable, and that the binary format is quicker and perceived as less complex. [ABSTRACT FROM AUTHOR]

Many quality characteristics of products or services are commonly evaluated on ordinal scales with a finite number of categories. A systematic analysis of categorical variables collected over time may be very useful for a profitable management strategy. In order to measure customer satisfaction or quality improvement in a process, two or more quality characteristics are often conjointly measured and summarized by suitable indexes. A common practice suggests evaluating a synthetic index by mapping each outcome of a multivariate ordinal variable into numbers. This procedure is not always legitimate from the measurement theory point of view. In this paper an alternative approach based on the algebraic theory of the ordered sets is proposed. This method avoids mapping multivariate components into numbers. Multivariate ordinal variable components are synthesized by ordering the multivariate sample space. The ordering criterion is defined on the basis of the specific characteristics of the process at hand. Practical effects in the use of this method are shown on a series of application examples. [ABSTRACT FROM AUTHOR]

This study investigated the extent to which two stakeholder groups of intercollegiate athletics (faculty and students) differed in the importance they attached to 10 selected goals and their approval of 11 selected processes within intercollegiate athletics. A total of 652 respondents (341 faculty, 311 students, 337 men, 310 women) from a large midwestern university responded to a questionnaire developed for this study. Results showed that subgroups, defined by faculty-student status, and gender differed significantly in most instances. These differences and the similarities in the rank ordering of the goals and processes are discussed. [ABSTRACT FROM AUTHOR]

Functional markers and their quantitative features (eg, maximum value, time to maximum, area under the curve [AUC], etc) are increasingly being used in clinical studies to diagnose diseases. It is thus of interest to assess the diagnostic utility of functional markers by assessing alignment between their quantitative features and an ordinal gold standard test that reflects the severity of disease. The concept of broad sense agreement (BSA) has recently been introduced for studying the relationship between continuous and ordinal measurements, and provides a promising tool to address such a question. Our strategy is to adopt a general class of summary functionals (SFs), each of which flexibly captures a different quantitative feature of a functional marker, and study its alignment according to an ordinal outcome via BSA. We further illustrate the proposed framework using three special classes of SFs (AUC‐type, magnitude‐specific, and time‐specific) that are widely used in clinical settings. The proposed BSA estimator is proven to be consistent and asymptotically normal given a consistent estimator for the SF. We further provide an inferential framework for comparing a pair of candidate SFs in terms of their importance on the ordinal outcome. Our simulation results demonstrate satisfactory finite‐sample performance of the proposed framework. We demonstrate the application of our methods using a renal study. [ABSTRACT FROM AUTHOR]

Pairwise comparison is a useful tool to express decision makers' (DMs') preferences in the group decision-making (GDM) problems. However, the preferences provided by pairwise comparisons could be self-contradictory, i.e., ordinal inconsistencies exist. Therefore, before reaching consensus, the first thing is to assure the DM's judgments that are not contradictory. As the purpose of the GDM is to choose most preferred alternative, the consensus degree for each alternative of all the DMs should be measured. In the present paper, an alternative consensus model for additive preference relations (APRs) based on ordinal consistency (OC) is developed. An algorithm is applied to detect and adjust the ordinally inconsistent elements for APRs. Then the alternative rankings for each ordinally consistent APR and the aggregated APR is obtained, respectively. A model is designed to change the DMs' importance, which increases the alternative consensus degree. The proposed model does not change the DMs' preferences, aiming to make full use of the DMs' judgements. Finally, an illustrative example and comparisons with the current approaches are furnished to demonstrate the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]