This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (...) (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4. (shrink)

Many clinical and psychological constructs are conceptualized to have multivariate higher-order constructs that give rise to multidimensional lower-order traits. Although recent measurement models and computing algorithms can accommodate item response data with a higher-order structure, there are few measurement models and computing techniques that can be employed in the context of complex research synthesis, such as meta-analysis of individual participant data or integrative data analysis. The current study was aimed at modeling complex item responses that can arise (...) when underlying domain-specific, lower-order traits are hierarchically related to multiple higher-order traits for individual participant data from multiple studies. We formulated a multi-group, multivariate higher-order item response theory (HO-IRT) model from a Bayesian perspective and developed a new Markov chain Monte Carlo (MCMC) algorithm to simultaneously estimate the (a) structural parameters of the first- and second-order latent traits across multiple groups and (b) item parameters of the model. Results from a simulation study support the feasibility of the MCMC algorithm. From the analysis of real data, we found that a bivariate HO-IRT model with different correlation/covariance structures for different studies fit the data best, compared to a univariate HO-IRT model or other alternate models with unreasonable assumptions (i.e., the same means and covariances across studies). Although more work is needed to further develop the method and to disseminate it, the multi-group multivariate HO-IRT model holds promise to derive a common metric for individual participant data from multiple studies in research synthesis studies for robust inference and for new discoveries. (shrink)

The experience of peer rejection in the classroom, an environment in which students spend a large part of their time, is accompanied by a sense of social pain which can have a profound effect on self-perception and attitude toward the overall school environment. These attitudes can be subsequently reflected in the student’s behavior at school and in his/her school success. The research aims to identify differences in the perception of school life (interpersonal and intrapersonal) among rejected and popular upper-primary school (...) students. For this purpose, the sociometric nomination method and a questionnaire measuring the student’s perception of the school environment were used. From a total of 1,625 students (aged 11–15) from 20 schools, 312 students with the status of popular (liked) and rejected (disliked) were included in the research. The multivariate analysis of covariance (with age and gender as covariates) results revealed no significant differences between the two contrasting groups (popular and rejected) in terms of the perception of school life (interpersonal and intrapersonal). The results of the research indicated a different perception of the school environmentwithinthe groups of rejected and popular students rather than differencesbetweenthe groups. Both the rejected and popular students report contradictory attitudes toward school life. Half of the students indicated that they feel lonely at school and have no confidence in teachers, considering the school a place where they do not like to learn, where they are troubled and where they do not like to talk to their classmates. Perhaps counterintuitively, a larger number of popular students stated that they feel lonely than did the rejected students from the class. Although the results do not paint a very positive picture of perceptions of the school environment, this should be seen as an opportunity to develop active class work with a greater emphasis on strengthening collective trust in the school. (shrink)

Based on the review and research on the teleworking modality and the variables that impact it at the organizational level, such as quality of life, communication, organizational culture or productivity, a case study is proposed under the innovation and teleworking model of a company. Japanese automotive industry for the application of Multivariate Analysis techniques such as Principal Component Analysis and Linear Regression, in order to condense the information provided by multiple variables into principal components and validate the (...) relationships and impact that exist between them, thus determining the interdependence and correlation of the same with the telework variable, allowing to simplify the complexity of sample spaces with many dimensions. It was possible to identify the main components with the variables' own labels and the dependent and predictive variables of the case were statistically validated, through the use of the IBM SPSS. (shrink)

One sector that severely suffers from the outbreak of the coronavirus is carsharing. The downswing of the carsharing industry may not only experience negative economic consequences but also ecological ones. Carsharing has the potential to reduce emissions, occupied space, and congestion and hence can actively contribute to mitigating climate change. As Bill Gates strikingly states: “Covid-19 is awful. Climate change could be worse.” For this reason, it is important to understand which underlying mechanisms drive carsharing usage during the Covid-19 pandemic. (...) The current research has the overall objective to provide deeper insights into the mediating mechanisms that explain carsharing usage intention during the Covid-19 pandemic. In particular, we draw on signaling theory to explore how different claims that prompt two different opposing underlying processes influence carsharing usage intention. An online experiment employing a 3 × 2 between-subjects design with participants acquired by the online panel platform Clickworker was conducted in April 2020. Fictitious labels and fictitious advertisements served as stimulus material and constituted the five experimental conditions. The data were analyzed by a multicategorial moderated mediation analysis and a multivariate analysis of covariance. Results reveal that environmental claims can stimulate perceived ecological benefits, which, in turn, positively affect carsharing usage intention. Interestingly, our research demonstrates that safety claims cannot decrease perceived physical risk in the context of Covid-19 and carsharing. Nevertheless, perceived physical risk has a negative influence on carsharing usage intention and hence should not be discarded altogether. The findings of this article offer new insights into the mental processes that guide consumer decision-making during the coronavirus crisis and also offer important policy implications by highlighting the relevance of environmental claims during the Covid-19 pandemic. Furthermore, the negative influence of perceived physical risk on carsharing usage intention points to the need for alternative measures to reduce users' risk perceptions. (shrink)

In their depictions of scandalized politicians, journalists frequently use news images that highlight the isolation of politicians. To test how this way of portraying political actors affects a recipient’s attitudes and his/her guilt perception toward such a scandalized politician an experiment was conducted. All participants were exposed to the identical textual information. However, the visual information was systematically altered. A multivariate analysis of covariance showed that participants – exposed to a visual highlighting the isolation of the politician (...) – evaluated the politician in a significantly more negative way and rated other recipients’ perceptions of the politician’s level of guilt to be higher. (shrink)

While many sociocultural, contextual, biological, behavioral, and psychological variables may contribute to the widespread under-representation of girls and women in the science, technology, engineering, and mathematics field, this study focused on STEM-gender stereotypes, school experiences, and adolescence as critical factors in driving students' interest and motivation in STEM. Based on this, the study investigated differences by gender and national context in adolescents' STEM-gender stereotypes, school empowerment, and school engagement in a preliminary step, and simultaneously examined how adolescents' STEM-gender stereotypes were (...) related to school empowerment and school engagement as well as to socioeconomic status. These latter relations were considered within the context of the potential moderating role of gender and national context. Participants included 213 Italian adolescents and 214 Nigerian adolescents, who completed measures of school empowerment and engagement, STEM-gender stereotypes, and SES. A multivariate analysis of covariance showed that Nigerian girls and boys reported significantly higher levels of school empowerment, school engagement, and STEM-gender stereotypes than their Italian peers. Moreover, regardless of the national context, boys scored significantly higher on school empowerment and STEM-gender stereotypes than girls. Furthermore, a multiple-group path analysis revealed how higher school empowerment was related to lower STEM-gender stereotypes in both Italian and Nigerian girls' groups, while higher school engagement was associated with lower STEM-gender stereotypes only in the Nigerian groups. Regardless of gender and nationality, higher SES was linked to lower STEM-gender stereotypes. These findings particularly suggest that school empowerment and school engagement can be relevant dimensions to be studied and to develop strategies to counteract STEM-gender stereotypes in adolescence. Nonetheless, gender and national context are key factors to be considered. Limitations, strengths, future research, and educational implications are discussed. (shrink)

Two alternative statistical approaches to modelling multi-level selection in nature, both found in the contemporary biological literature, are contrasted. The simple covariance approach partitions the total selection differential on a phenotypic character into within-group and between-group components, and identifies the change due to group selection with the latter. The contextual approach partitions the total selection differential into different components, using multivariate regression analysis. The two approaches have different implications for the question of what constitutes group selection and (...) what does not. I argue that the contextual approach is theoretically preferable. This has important implications for a number of issues in the philosophical debate about the levels of selection. Introduction Group selection and the covariance formulation of selection The contextual approach A modification of the simple covariance approach Consequences: frameshifting and additivity 5.1 Frameshifting 5.2 Additivity Conclusion. (shrink)

BackgroundMental illness among Malaysian children is gradually reaching a fundamentally alarming point as it persistently shows increasing trend. The existing literature on the etiologies of children’s mental illness, highlights the most common cause to be ineffective or impaired parenting. Thus, efforts to combat mental illness in children should focus on improving the quality of parenting. Documented interventional studies focusing on this issue, particularly in Malaysia, are scarce and commonly report poor treatment outcomes stemming from inconvenient face-to-face instructions. Consequently, proposing an (...) accessible online and digital-assisted parenting program is expected to reach a larger number of parents, as it can overcome substantial barriers. Hence, this study aims to develop a universal digital-assisted preventive parenting intervention called DaPI, that aims to enhance mental health of children in Malaysia.MethodsA total of 200 parents of children aged 10–14 years will be recruited and randomized into two groups either intervention or waitlist-control based on a 1:1 ratio for a duration of 8 weeks. Those in the intervention group will receive eight sessions of the DaPI program that focus mainly on parenting and children’s mental health. The primary outcome of this study will essentially focus on the changes in parent-reported parenting behavior and parental self-efficacy. The secondary outcome will be changes in children’s mental health. Assessments will be arranged pre- and post-intervention as well as at the 1-month follow-up. Analyses will be conducted using a paired t-test and multivariate analysis of covariance.DiscussionThe expected outcome will be the establishment of DaPI in promoting children’s mental health by targeting changes in parenting behavior and parental self-efficacy in Malaysia. Findings from this study will be beneficial for policymakers to invest in parenting programs that could provide support to parents in enhancing their child’s overall development.Clinical trial registration[www.irct.ir], identifier [IRCT20211129053207N1]. (shrink)

BackgroundInformation processing speed is a marker for cognitive function. It is associated with neural maturation and increases during development. Traditionally, IPS is measured using paper and pencil tasks requiring fine motor skills. Such skills are often impaired in patients with neurological conditions. Therefore, an alternative that does not need motor dexterity is desirable. One option is the computerized symbol digit modalities test, which requires the patient to verbally associate numbers with symbols.MethodsEighty-six participants were examined, 38 healthy and 48 hospitalized for (...) a non-neurological disease. All participants performed the written SDMT, c-SDMT, and the Test of Non-verbal Intelligence Fourth Edition. Statistical analyses included a multivariate analysis of covariance for the effects of intelligence and hospitalization on the performance of the SDMT and c-SDMT. A repeated measures analysis of variance was used to compare performance across c-SDMT trials between inpatients and outpatients.ResultsThe MANCOVA showed that hospitalization had a significant effect on IPS when measured with the SDMT but not with the c-SDMT, while IQ had no effect on IPS. Age was the best predictor of performance of both tests. The repeated measures ANOVA revealed no significant difference in within-test performance between outpatient and inpatient participants in the c-SDMT.ConclusionPerformance of the c-SDMT is not confounded by hospitalization and gives within-test information. As a valid and reliable measure of IPS for children and adolescents, it is suitable for use in both inpatient and outpatient populations. (shrink)

Objective: The aim of this study was to examine the psychometric properties and factorial structure of the Schema Mode Inventory for Eating Disorders (SMI-ED) in a disordered eating population. Method: 573 participants with disordered eating patterns as measured by the Eating Disorder Examination Questionnaire (EDE-Q) completed the 190-item adapted version of the Schema Mode Inventory (SMI). The new SMI-ED was developed by clinicians/researchers specializing in the treatment of eating disorders, through combining items from the original SMI with a set of (...) additional questions specifically representative of the eating disorder population. Psychometric testing included Confirmatory Factor Analysis (CFA) and internal consistency (Cronbach’s α). Multivariate Analyses of Covariance (MANCOVA) was also run to test statistical differences between the EDE-Q subscales on the SMI-ED modes, while controlling for possible confounding variables. Results: Factorial analysis confirmed an acceptable sixteen-related-factors solution for the SMI-ED, thus providing preliminary evidence for the adequate validity of the new measure based on internal structure. Concurrent validity was also established through moderate to high correlations on the modes most relevant to eating disorders with EDE-Q subscales. This study represents the first step in creating a psychometrically sound instrument for measuring schema modes in eating disorders, and provides greater insight into the relevant schema modes within this population. Conclusion: This research represents an important preliminary step toward understanding and labeling the schema mode model for this clinical group. Findings from the psychometric evaluation of SMI-ED suggest that this is a useful tool which may further assist in the measurement and conceptualization of schema modes in this population. (shrink)

This, the third edition of Fundamentals of Experimental Design, has five added chapters - those on regression (Chapters 12, 14, and 15), multivariate analysis (Chapter 18), and the matrix algebra appropriate to the level of presentation of this material (Chapter 13). I have noted in the preface other additions in this third edition. The added material should enhance the value of the book as a textbook and a reference. Given these additions, however, alternative approaches in using the current (...) edition as a textbook may merit consideration. It may help to note that Chapters 16 and 17 (analysis of covariance, trend analysis) do not depend on the material in Chapters 12 through 15, although the student should know something about simple linear regression to be able to understand fully the material in Chapters 16 and 17. In any event, the instructor who wants to teach only the material in the first two editions can do so by dropping the added chapters - 12 through 15, and 18 - from the syllabus. (shrink)

Objective: Tangent Space Mapping using the geometric structure of the covariance matrices is an effective method to recognize multiclass motor imagery. Compared with the traditional CSP method, the Riemann geometric method based on TSM takes into account the nonlinear information contained in the covariance matrix, and can extract more abundant and effective features. Moreover, the method is an unsupervised operation, which can reduce the time of feature extraction. However, EEG features induced by MI mental activities of different subjects (...) are not the same, so selection of subject-specific discriminative EEG frequency components play a vital role in the recognition of multiclass MI. In order to solve the problem, a discriminative and multi-scale filter bank tangent space mapping algorithm is proposed in this article to design the subject-specific Filter Bank so as to effectively recognize multiclass MI tasks. Methods: On the 4-class BCI competition IV-2a dataset, first, a non-parametric method of multivariate analysis of variance based on the sum of squared distances is used to select discriminative frequency bands for a subject; next, a multi-scale FB is generated according to the range of these frequency bands, and then decompose multi-channel EEG of the subject into multiple sub-bands combined with several time windows. Then TSM algorithm is used to estimate Riemannian tangent space features in each sub-band and finally a liner Support Vector Machines is used for classification. Main Results: The analysis results show that the proposed discriminative FB enhances the multi-scale TSM algorithm, improves the classification accuracy and reduces the execution time during training and testing. On the 4-class BCI competition IV-2a dataset, the average session to session classification accuracy of nine subjects reached 77.33 ± 12.3%. When the training time and the test time are similar, the average classification accuracy is 2.56% higher than the latest TSM method based on multi-scale filter bank analysis technology. When the classification accuracy is similar, the training speed is increased by more than three times, and the test speed is increased two times more. Compared with Supervised Fisher Geodesic Minimum Distance to the Mean, another new variant based on Riemann geometry classifier, the average accuracy is 3.36% higher, we also compared with the latest Deep Learning method, and the average accuracy of 10-fold cross validation improved by 2.58%. Conclusion: Research shows that the proposed DMFBTSM algorithm can improve the classification accuracy of MI tasks. Significance: Compared with the MFBTSM algorithm, the algorithm proposed in this article is expected to select frequency bands with good separability for specific subject to improve the classification accuracy of multiclass MI tasks and reduce the feature dimension to reduce training time and testing time. (shrink)

The application of multiple regression and path analysis is discussed in regard to the exclusive use of the beta coefficients. Beta is one of the possible ways of controlling for the effects of the remaining predictors, others are part and partial correlation, part and partial covariance. A typology is developed for the difference between total and controlled effect. With this instrument (for controlled effect = beta) it can be shown under which conditions the sum of the total explaining (...) power (r2y,xi) and the sum of the additional explaining power (Part correlation2) do exceed or not Multiple R2. By the criteria of sign rule and of the relative advantages of the decomposition of total effect in controlled effect and rest effect it is argued that beta is still the best way (of those considered) of control. Next some problems of the otherwise recommended LISREL approach are discussed: Estimation, data-fitting versus model test, model-fitting, standardization. Finally some parallels between models for metric and models for non-metric data are specified. (shrink)

A result from a standard linear model course is that the variance of the ordinary least squares (OLS) coefficient of a variable will never decrease when including additional covariates into the regression. The variance inflation factor (VIF) measures the increase of the variance. Another result from a standard linear model or experimental design course is that including additional covariates in a linear model of the outcome on the treatment indicator will never increase the variance of the OLS coefficient of the (...) treatment at least asymptotically. This technique is called the analysis of covariance (ANCOVA), which is often used to improve the efficiency of treatment effect estimation. So we have two paradoxical results: adding covariates never decreases the variance in the first result but never increases the variance in the second result. In fact, these two results are derived under different assumptions. More precisely, the VIF result conditions on the treatment indicators but the ANCOVA result averages over them. Comparing the estimators with and without adjusting for additional covariates in a completely randomized experiment, I show that the former has smaller variance averaging over the treatment indicators, and the latter has smaller variance at the cost of a larger bias conditioning on the treatment indicators. Therefore, there is no real paradox. (shrink)

Systematic sampling of communities gives rise to large contingency tables summing up possible changes in the assemblages' structure. Such tables are generally analysed by multivariate statistical methods, which are ill-suited for simultaneously analysing rare and common species (Field et al., 1982). In order to separately process species belonging to either of these categories, we propose a statistical method to select common species in a sequence of ecological surveys. It is based on a precise definition of rarity, and depends on (...) a rarity parameter. In this work, this parameter will be optimised so that the sub-table of common species captures the essential features of the complete table as well as possible. In this way we analysed the spatio-temporal evolution of macrobenthic communities from the Algiers harbour to study the pollution influence during a year. The examination of the communities' structuring was done through Principal Components Analysis (PCA) of the species proportions table. Environmental variables were simultaneously sampled. We show that the data structure can be explained by about 25% of the total number of present species. Two environmental gradients were brought to the fore inside the harbour, the first one representing pollution, and the second one representing hydrological instabilities. (shrink)

The growth in organic and local foods consumption has been examined using two different approaches to identify characteristics and motivations of food shoppers: market segmentation and economic models using multivariate analysis. The former approach, based on Means-end Chain theory, examines how intrinsic characteristics of foods affect food choices. The latter microeconomic approach examines economic constraints and extrinsic factors. This study demonstrates value in combining the two approaches to generate better empirical predictions of who buys organic and local food. (...) It also supports a broader theoretical framework to explain behavior in terms of intrinsic and extrinsic motivations. Using US data, an adaptation of the Food Related Lifestyle model yields four consumer lifestyles segmented by intrinsic motivations related to food. Each consumer segment exhibits distinct organic and local foods consumption behaviors. A multinomial logit model is estimated to examine the probability of being in one of these four groups as a function of extrinsic variables and economic constraints. In support of Alphabet theory and Regulatory Focus theory, we find that inclusion of extrinsic factors improves prediction of behavior and the ability to explain why they buy organic and local foods. The extrinsic variables that significantly increase the probability of being in a particular consumer food lifestyle segment include: environmental concerns, health practices, race, the presence of a farmers’ market, and to a lesser degree, family composition and income. We also find regulatory focus is most pronounced among the most active organic and local food shoppers. (shrink)

BackgroundNew metrics have been developed to assess the impact of research and provide an indication of online media attention and data dissemination. We aimed to describe online media attention of articles evaluating cancer treatments and identify the factors associated with high online media attention.MethodsWe systematically searched MEDLINE via PubMed on March 1, 2015 for articles published during the first 6 months of 2014 in oncology and medical journals with a diverse range of impact factors, from 3.9 to 54.4, and selected (...) a sample of articles evaluating a cancer treatment regardless of study design. Altmetric Explorer was used to identify online media attention of selected articles. The primary outcome was media attention an article received online as measured by Altmetric score (i.e., number of mentions in online news outlets, science blogs and social media). Regression analysis was performed to investigate the factors associated with high media attention, and regression coefficients represent the logarithm of ratio of mean (RoM) values of Altmetric score per unit change in the covariate.ResultsAmong 792 articles, 218 (27.5%) received no online media attention (Altmetric score = 0). The median [Q1–Q3] Altmetric score was 2.0 [0.0–8.0], range 0.0–428.0. On multivariate analysis, factors associated with high Altmetric score were presence of a press release (RoM = 10.14, 95%CI [4.91–20.96]), open access to the article (RoM = 1.48, 95%CI [1.02–2.16]), and journal impact factor (RoM = 1.10, 95%CI [1.07–1.12]. As compared with observational studies, systematic reviews were not associated with high Altmetric score (RoM = 1.46, 95%CI [0.74–2.86]; P = 0.27), nor were RCTs (RoM = 0.65, 95%CI [0.41–1.02]; P = 0.059) and phase I/ii non-RCTs (RoM = 0.58, 95%CI [0.33–1.05]; P = 0.07). The articles with abstract conclusions favouring study treatments were not associated with high Altmetric score (RoM = 0.97, 95%CI [0.60–1.58]; P = 0.91).ConclusionsMost important factors associated with high online media attention were the presence of a press release and the journal impact factor. There was no evidence that study design with high level of evidence and type of abstract conclusion were associated with high online media attention. (shrink)

Emotions change over time. A comprehensive understanding of emotions will require that their temporal nature be observed and analysed. By observing emotion over time, one can disentangle and simultaneously analyse temporal variability within individuals and between-individual variability using a two-step process approach. First, within-person temporal patterns (e.g., covariation, lead–lag relation, periodicity, etc.) are assessed for each subject. Second, between-person analyses are conducted on the within-person patterns. These two steps can be done simultaneously with hierarchical linear models (HLM) or in two (...) actual steps with the process approach. HLM is limited to the intra-individual analysis of linear patterns (e.g., slope, intercept), whereas the process approach can be used to examine non-linear aspects of intra-individual change, such as multivariate patterns, within-subject skew, or phase relations between oscillating processes. In this paper we provide a description of the process approach and present several examples of, as well as suggestions for, intra-individual analysis applied to emotion and individual differences. (shrink)

The purpose of this study was to examine the determinants for early discontinuation among IUCD users in a rural district of northern India. Multivariate analysis indicated several significant predictors of early discontinuation of IUCD use. The risk of discontinuation increased more than two times in the presence of factors such as more than usual amount of menstrual flow before insertion and intermenstrual bleeding after insertion. Similarly, residence or alternatively those coming from villages without health centres were nearly two (...) times more likely to discontinue. Menstrual disturbance increased the risk nearly three-fold. If only those women who report normal menstrual cycles had IUCDs inserted, it is very likely that the high discontinuation rate due to menstrual disturbance could be reduced. Knowledge about the IUCD and its effectiveness decreased the risk of early discontinuation but was not a statistically significant factor in multivariate analysis. Validation of the developed model was done by using the bootstrapping method and the model was found to be 18% noisy. These findings may help family planning providers in counselling and practice. (shrink)

While univariate functional magnetic resonance imaging data analysis methods have been utilized successfully to map brain areas associated with cognitive and emotional functions during viewing of naturalistic stimuli such as movies, multivariate methods might provide the means to study how brain structures act in concert as networks during free viewing of movie clips. Here, to achieve this, we generalized the partial least squares analysis, based on correlations between voxels, experimental conditions, and behavioral measures, to identify large-scale neuronal (...) networks activated during the first time and repeated watching of three ∼5-min comedy clips. We identified networks that were similarly activated across subjects during free viewing of the movies, including the ones associated with self-rated experienced humorousness that were composed of the frontal, parietal, and temporal areas acting in concert. In conclusion, the PLS method seems to be well suited for the joint analysis of multi-subject neuroimaging and behavioral data to quantify a functionally relevant brain network activity without the need for explicit temporal models. (shrink)

The aim of this study was to examine the influence of somatic maturation in anthropometric, physical, and game-related variables in youth basketball age groups under-13 and under-15. One-hundred and eighty-five basketball players performed anthropometrical and physical tests during a non-official youth basketball tournament. Predicted maturity offset and game-related variables were also analyzed. Cluster analysis was used to analyze the between-maturation status differences in all parameters in each age group. Also, regularized generalized canonical correlation analysis was used to assess (...) relative contributions of maturational, physical, and game-related variables within each age group. Based on MO, two different clusters were identified within each age category. Greater differences in MO were identified among U-13 clusters than among U-15 clusters. No significant differences were observed between clusters in terms of physical and game-related variables. High correlations between maturational, physical, and game-related variables were found for boys. In girls, different trends in terms of correlations were observed. The strongest association between blocks was observed between physical tests and game-related variables in all age categories, except for U-15 girls. Knowing and identifying performance profiles according to biological age is of upmost importance since it allows the coach to create challenging situations adjusted to the individual’s needs. (shrink)

Mazur & Booth (1998) (M&B) suggested that high testosterone (T) relates to status, dominance, and (anti-) social behaviour. However, low T also relates to status and to formal dominance. The General Trait Covariance (GTC) model predicts both relations under the assumption that high and low T modulates the genotype in ways that enforce the development of almost polar covariant patterns of body, brain, intellectual, and personality traits, irrespective of race. The precise modelling of these dose-dependent molecular body-intelligence-personality-behaviour relations requires (...) that causes, mechanisms, and effects enjoy equal operational standing. (shrink)

In sprint track events, the starting reaction time is an important professional capacity of the athletes, and it is closely related to their performance. This study examines the reaction time and the results of the male and female sprinters participating in the World Athletics Championships from 2011 to 2019 in the 100 m, 200 m, 100 m, and 110 m hurdles. The researchers used least squares estimation, multivariate analysis of variance, and other methods and theories to construct a (...) double logarithmic model and a multivariate analysis of a variance model. The researchers used Econometrics Views and SPSS software programs to analyze the correlation between the performance and the starting reaction time, as well as the patterns in the changes of the reaction time of athletes of both genders in different types of and rounds in the competitions. Research results show that there is a direct correlation between the reaction time and the performance, and the degrees of correlation vary depending on the gender of the athlete, year of competition, type of competition, and round of competition. There is a correlation between the foul types and the type of competition, but there is no correlation between foul types and the gender of the athlete. The research results are science-based and are of practical value and thus can be used as a reference by coaches in sprint running to offer more professional guidance to the athletes. (shrink)

We investigated whether, in the emergency department, educational video-assisted informed consent is superior to the conventional consent process, to inform trauma patients undergoing surgery about the procedure, benefits, risks, alternatives, and postoperative care. We conducted a prospective randomized controlled trial, with superiority study design. All trauma patients scheduled to receive trauma-related debridement surgery in the ED of Kaohsiung Medical University Hospital were included. Patients were assigned to one of two education protocols. Participants in the intervention group watched an educational video (...) illustrating informed consent information, whereas those in the control group read an informed consent document. The primary outcome was knowledge scores and the secondary outcome was assessment of patient satisfaction. A multivariable regression model, with predefined covariates, was used to analyze differences in knowledge scores and patient satisfaction levels between the groups. A total of 142 patients were enrolled, with 70 and 72 assigned to the intervention and control groups, respectively. Mean knowledge scores were higher in the intervention ) than in the control group. By multivariate analysis, the intervention group had significantly greater differences in knowledge scores. Age, injury severity score, and baseline knowledge score significantly affected the differences in knowledge scores. Significant improvements were observed in patients’ perception of statements addressing comprehension of the information provided, helpfulness of the supplied information for decision making, and satisfaction with the informed consent process. Multivariate analysis showed significant correlations between video education and patient satisfaction. Both the educational approach and severity of injury may have an impact on patient understanding during the informed consent process in an emergency environment. Video-assisted informed consent may improve the understanding of surgery and satisfaction with the informed consent process for trauma patients in the ED. Institutions should develop structured methods and other strategies to better inform trauma patients, facilitate treatment decisions, and improve patient satisfaction. The ClinicalTrials.gov Identifier is NCT01338480. The date of registration was April 18, 2011. (shrink)

Background: To evaluate the effectiveness of a multifaceted intervention in improving emergency department (ED) patient privacy and satisfaction in the crowded ED setting. Methods: A pre- and post-intervention study was conducted. A multifaceted intervention was implemented in a university-affiliated hospital ED. The intervention developed strategies to improve ED patient privacy and satisfaction, including redesigning the ED environment, process management, access control, and staff education and training, and encouraging ethics consultation. The effectiveness of the intervention was evaluated using patient surveys. Eligibility (...) data were collected after the intervention and compared to data collected before the intervention. Differences in patient satisfaction and patient perception of privacy were adjusted for predefined covariates using multivariable ordinal logistic regression. Results: Structured questionnaires were collected with 313 ED patients before the intervention and 341 ED patients after the intervention. There were no important covariate differences, except for treatment area, between the two groups. Significant improvements were observed in patient perception of "personal information overheard by others", being "seen by irrelevant persons", having "unintentionally heard inappropriate conversations from healthcare providers", and experiencing "providers' respect for my privacy". There was significant improvement in patient overall perception of privacy and satisfaction. There were statistically significant correlations between the intervention and patient overall perception of privacy and satisfaction on multivariable analysis. Conclusions: Significant improvements were achieved with an intervention. Patients perceived significantly more privacy and satisfaction in ED care after the intervention. We believe that these improvements were the result of major philosophical, administrative, and operational changes aimed at respecting both patient privacy and satisfaction. (shrink)

Structural equation model is a multivariate statistical analysis method. It can not only test some unpredictable abstract ideas, but also design parameters for the causal connection model between independent variables and dependent variables. Among them, the analysis of various latent variables is based on the verification factor analysis technology. The research first collects various relevant data, derives the latent variables and measurement variables, then composes the measurement model, and then verifies the adaptability of the measurement model (...) structure mode through actual data collection. When such suitable factors are determined, a causal model based on path analysis technology for latent variables, that is, a structural model, can be used for parameter design. This article uses the structural equation model as an analysis tool, starting from the three aspects of teachers, cases, and students to evaluate the application effect of the case teaching method in the classroom teaching of intellectual property law course and construct a structural equation model of the influencing factors of the case teaching effect. To understand students’ satisfaction with case teaching effects and related influencing factors, the research results show that the effect of case teaching is jointly affected by the level of teachers, case selection, and student response. Among them, teacher factors have the greatest impact on case teaching effects, followed by case factors, and students have the least. (shrink)

Objective Analyze racial differences in comfort with medical research using an alternative to the traditional approach that treats white people as a raceless norm.Methods Quantitative analysis of survey responses (n = 1,570) from Black and white residents of the US to identify relationships between perceptions of research as a right or a risk, and comfort participating in medical research.Results A lower proportion of white respondents reported that medical experimentation occurred without patient consent (p < 0.001) and a higher proportion (...) of white respondents reported that it should be their right to participate in medical research (p = 0.02). Belief in one’s right to participate was significantly predictive of comfort (b = 0.37, p < 0.001). Belief in experimentation without consent was significantly predictive of comfort for white respondents but not for Black respondents in multivariable analysis.Conclusions A rights-based orientation and less concern about the risks of medical research among white respondents demonstrate comparative advantage. Efforts to diversify medical research may perpetuate structural racism if they do not (1) critically engage with whiteness and its role in comfort with participation, and (2) identify and respond specifically to the needs of Black patients. (shrink)

IntroductionIn highly developed countries, as many as 16 percent of children are physically abused each year. Traumatic brain injury (TBI) is the most common injury in non-accidental trauma (NAT) and is responsible for 80 percent of fatal NAT cases, with most deaths occurring in children younger than three years old. Cases of abusers who refuse withdrawal of life-sustaining medical treatment (LSMT) to avoid criminal charges have previously been reported. Therefore, we hypothesized that NAT is associated with a lower risk for (...) withdrawal LSMT in pediatric TBI.MethodsThe pediatric Trauma Quality Improvement Program database was analyzed (2014 to 2016) for patients aged 16 and younger with TBI and Glasgow Coma Scale (GCS) of 8 and lower on admission. Patients with a head Abbreviated Injury Scale (AIS) of 2 or less or who died within 48 hours were excluded. A multivariable logistic regression model was used for analysis.ResultsOf 2,209 TBI patients, 92 (4.2 percent) had withdrawal of LSMT. Compared to those without withdrawal of LMST, those with LMST had statistically similar median age (three years of age versus seven years, p = 0.07) and a higher rate of NAT (33.7 percent versus 13.5 percent, p < 0.001). The most common specified perpetrator was a father/stepfather/ male partner (70 percent). After adjusting for covariates, factors associated with higher risk for withdrawal of LSMT included age of less than three years (OR 2.38, CI 1.34-4.23, p < 0.05) and NAT (OR 1.86, CI 1.02-3.41, p < 0.05).ConclusionNAT is associated with increased risk for withdrawal of LSMT in pediatric TBI. Age of less than three years is similarly associated with a higher risk for withdrawal of LSMT. Future research in this population is needed to determine what other factors predict withdrawal of LSMT and what resources, such as social workers and/or ethics consults, are utilized. (shrink)

If the words of natural human language possess a universal positivity bias, as assumed by Boucher and Osgood’s (1969) famous Pollyanna hypothesis and computationally confirmed for large text corpora in several languages (Dodds et al., 2015), then children and youth literature (CYL) should also show a Pollyanna effect. Here we tested this prediction applying a vector space model- based sentiment analysis tool called SentiArt (Jacobs, 2019) to two CYL corpora, one in English (372 books) and one in German (500 (...) books). Pitching our analysis at the sentence level, and assessing semantic as well as lexico-grammatical information, bBoth corpora show the Pollyanna effect and thus add further evidence to the universality hypothesis. The results of our multivariate sentiment analyses provide interesting testable predictions for future scientific studies of literature. (shrink)

Fractal fluctuations are a core concept for inquiries into human behavior and cognition from a dynamic systems perspective. Here, we present a generalized variance method for multivariate detrended fluctuation analysis (mvDFA). The advantage of this extension is that it can be applied to multivariate time series and considers intercorrelation between these time series when estimating fractal properties. First, we briefly describe how fractal fluctuations have advanced a dynamic system understanding of cognition. Then, we describe mvDFA in detail (...) and highlight some of the advantages of the approach for simulated data. Furthermore, we show how mvDFA can be used to investigate empirical multivariate data using electroencephalographic recordings during a time-estimation task. We discuss this methodological development within the framework of interaction-dominant dynamics. Moreover, we outline how the availability of multivariate analyses can inform theoretical developments in the area of dynamic systems in human behavior. (shrink)

Using the classroom as the unit of analyses, the current article discusses the methodological issues surrounding the literature with regard to the study of academic misconduct. Arguing for a shift in research, the present empirical investigation assesses the relationship between students' perceptions of classroom environment and academic misconduct by utilizing valid and reliable multidimensional measures with established constructs. By utilizing the classroom as the unit of analysis, a better understanding of the unique variance in academic dishonesty across classes may (...) be established in relation to variation in students' perceptions of teaching practices. One hundred twenty-eight classes participated in the current study, with 3,151 students completing the Students' Perceptions of Teacher Effectiveness survey and Academic Misconduct Survey. Although students' overall perceptions of teacher effectiveness were not related to the rate of academic misconduct across classes, results do suggest that the lower the difficulty and workload of the course is perceived as being, the more likely students report cheating on exams, taking credit for others' work, using false personal excuses, and creatively padding their work. Reasons for these relationships are explicated, and suggestions for future research are discussed. (shrink)

Cook et al. overstate the evidence supporting their associative account of mirror neurons in humans: most studies do not address a key property, action-specificity that generalizes across the visual and motor domains. Multivariate pattern analysis of neuroimaging data can address this concern, and we illustrate how MVPA can be used to test key predictions of their account.

How to make use of the leaders’ psychological capital to improve the innovation behavior of employees is an important issue for the talent management of enterprises today, and it is also the goal that enterprises must pursue if they want to stand out in the fierce competition. Therefore, in this study, 154 enterprises in high-tech area were selected for questionnaire survey. The correlation between lead-member exchange (LMX) relationship (emotion, loyalty, contribution, professional respect), leaders' psychological capital (confidence, hope, optimism, tenacity), and (...) employees' innovation behaviors were analyzed by multivariate regression. Hierarchical regression method was used to examine the mediating effect of the LEX. It was found that confidence, toughness, and contribution were significantly positively correlated with employee innovation behavior (P<0.000). The positive correlation between hope, optimism, emotion, and loyalty with employees' innovation behavior was significant (P<0.05). Emotion, loyalty, and contribution had mediating effects on the leaders’ psychological capital and the innovation behavior of employees. In conclusion, the leaders’ psychological capital can have a significant positive effect on the innovation behavior of employees directly, and it can also have an indirect positive effect on the innovation behavior of employees by maintaining high quality LMX. (shrink)

Analysis of Emmy Noether's 1918 theorems provides an illuminating method for testing the consequences of coordinate generality, and for exploring what else must be added to this requirement in order to give general covariance its far-reaching physical significance. The discussion takes us through Noether's first and second theorems, and then a third related theorem due originally to F. Klein. Contact will also be made with the contributions of, principally, J.L. Anderson, A. Trautman, P.A.M. Dirac, R. Torretti and the (...) father of the whole business, A. Einstein. (shrink)

Since its introduction, multivariate pattern analysis, or ‘neural decoding’, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder’s dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: (...) decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction 2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis? 2.2The informational benefits of multivariate pattern analysis 3Why the Decoder’s Dictum Is False 3.1We don’t know what information is decoded 3.2The theoretical basis for the dictum 3.3Undermining the theoretical basis 4Objections and Replies 4.1Does anyone really believe the dictum? 4.2Good decoding is not enough 4.3Predicting behaviour is not enough 5Moving beyond the Dictum 6Conclusion. (shrink)