ASSESSMENT OF LOCAL INFLUENCE IN A GROWTH CURVE MODEL WITH RAO'S SIMPLE COVARIANCE STRUCTURE

The present paper deals with the problem of assessing the local influence in a growth curve model with Rao's simple covariance structure. Based on the likelihood displacement,the curvature measure is employed to evaluate the effects of some minor perturbations on the statistical inference, thus leading to the large curvature direction, which is the most critical diagnostic statistic in the context of the local influence analysis. As an application, the common covariance-weighted perturbation scheme is thoroughly considered.

Hypothesis Testing for Independence Under Blocked Compound Symmetric Covariance Structure

One type of covariance structure is known as blocked compound symmetry.Recently,Roy et al.(J Multivar Anal 144:81–90,2016)showed that,assuming this covariance structure,unbiased estimators are optimal under normality and described hypothesis testing for independence as an open problem.In this paper,we derive the distributions of unbiased estimators and consider hypothesis testing for independence.Representative test statistics such as the likelihood ratio criterion,Waldstatistic,Rao’s score statistic,and gradient statistic are derived,and we evaluate the accuracy of the test using these statistics through numerical simulations.The power of the Wald test is the largest when the dimension is high,and the power of the likelihood ratio test is the largest when the dimension is low.

Fermionic Covariant Prolongation Structure for a Super Nonlinear Evolution Equation in 2+1 Dimensions

The integrability of a （2＋1）-dimensional super nonlinear evolution equation is analyzed in the framework of the fermionie covariant prolongation structure theory. We construct the prolongation structure of the multidimen- sional super integrable equation and investigate its Lax representation. Furthermore, the Backlund transformation is presented and we derive a solution to the super integrable equation.

Factors Related to LGBT Recognition for University Students and Employed Adults

Background: The aim of this study was to investigate Japanese students and employed adults’ characteristic features, and sexual situation, and to find the correlated factors of lesbian, gay, bisexual, transgender (LGBT) recognition in order to obtain suggestions for improved relationships with sexual minorities in a diversifying society. Methods: This quantitative cross-sectional descriptive correlational study occurred during 2018 to 2019 when 2210 questionnaires were distributed to a purposive sample of eligible participants. A total of 1534 completed questionnaires (69.4%) were returned, of which 1439 (65.1%) were suitable for analyses. The survey included respondents’ 1) characteristics, 2) sexual situation, and 3) LGBT recognition scale. Data were analyzed with descriptive statistics, factor analysis, reliability analysis, and structural equation modeling. SPSS ver. 26.0 (SPSS, Chicago, IL, USA) was used for data analysis at a 5% significance level. Results: The LGBT recognition score was significantly affected by suffering from gender identity (standardized partial regression coefficient: β = 0.17, p < 0.001), age (β = −0.19, p < 0.001), learning about LGBT experience (β = 0.29, p < 0.001), experience of disclosure from LGBT person (β = 0.14, p < 0.001), sexual problems with intimate relationship (β = 0.07, p < 0.001), and diversity penetration (β = 0.14, p < 0.05). Conclusions: Suffering from gender identity, learning about LGBT experience, experience of disclosure from LGBT person, sexual problem with intimate relationship, and diversity penetration had a positive effect, whereas age had negative effects on the LGBT recognition score.

Structural covariance network of the hippocampus–amygdala complex in medication-nale patients with first-episode major depressive disorder

Background The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder(MDD).Each of these structures consists of several heterogeneous subfields.We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus–amygdala complex in medication-nale patients with first-episode MDD.Methods High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode,medication-nale,and noncomorbid MDD patients and 81 age-,sex-,and education level-matched healthy control participants(HCs).The structural covariance network(SCN)was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions;the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions,controlled for age,sex,education level,and intracranial volume.The global and nodal graphmetrics were calculated and compared between groups.Results Compared with HCs,the SCN within the hippocampus–amygdala complex in patients with MDD showed a shortened mean characteristic path length,reduced modularity,and reduced small-worldness index.At the nodal level,the left hippocampal tail showed increased measures of centrality,segregation,and integration,while nodes in the left amygdala showed decreased measures of centrality,segregation,and integration in patients with MDD compared with HCs.Conclusion Our results provide the first evidence of atypical topologic characteristics within the hippocampus–amygdala complex in patients with MDD using structure network analysis.It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.

COVARIANCE STRUCTURAL ANALYSIS WITH POLYTOMOUS VARIABLES IN SEVERAL POPULATIONS

In this paper, covariance structures with polytomous variables in several populations are analyzed. A computationally efficient multistage procedure is proposed to estimate the thresholds and the covariance structure parameters.Statistical properties of the estimators are derived, and a computer program is implemented to obtain the solution. An artificial example is presented to illustrate the method.

Perception of people for the risk of Tianwan nuclear power plant

A questionnaire survey of residents’risk perceptions related to Taiwan nuclear power plant in China was carried out to explore the determining factors that affect individual risk perception.This study proposed to pursue a more comprehensive understanding of factors that affected individual risk perception to nuclear power plants.Covariance structure analysis was conducted using risk perceptions of nuclear power as dependent variable and including interest and knowledge levels of nuclear power,acceptability,benefit perception,trust in nuclear power operation,and trust in government as independent variables.The use of the hypothesis of Elaboration likelihood model(ELM)was also proposed.The results showed that persons with higher levels of interest and knowledge of nuclear power had their own perceptions of risk closely associated with acceptability and potential benefits of nuclear power.In contrast,persons with no interest in and knowledge of nuclear power would have risk perceptions related to their trust in nuclear operation and the government,which partially supported the ELM hypothesis.All these results indicated that the government in China plays an important role in rational risk perceptions,and well-designed communication of risks will help the public to be involved in risk management and improve people’s rational acceptance of risk.