Multiple Statistical Procedures Research Articles

Chinese adolescents’ mental health status and their coping strategy use in COVID-19

This study investigated the relationships between Chinese adolescents’ mental health status and their coping strategy use in the context of the Coronavirus Disease 2019 (COVID-19). A total of 4579 participants answered two questionnaires, and data were analyzed through multiple statistical procedures, including Pearson correlation test and one-way ANOVA. The findings show that COVID-19 generally had minor effects on the mental health of the participants and problem-solving was reported as an effective strategy to tackle the stressors caused by the pandemic. Additionally, avoiding, help-seeking and patience demonstrated similar frequency across participants and fantasying was used the most by those with severe mental health status. These findings will shed some light into how educators provide effective mental health instructions for students, and concomitantly will help in tailoring early interventions that would mitigate the adverse effects of disasters like COVID-19 on adolescents and beyond.

Attitudes and Concerns of Pre-Service Teachers’ about Inclusive Education Enshrined in the New Four-Year Basic Education Curriculum in Ghana


 
 
 
 Inclusive education, that is, the inclusion of learners with special educational needs and disabilities into regular schools is now one of the most significant core pillars in the New Bachelor of Education (Basic Education) Curriculum for teacher education in Ghana. In order to address this issue, pre-service teachers in their first year per the curriculum are introduced to inclusive education as a subject. The study aimed at finding out the attitude and concerns of pre-service teachers towards inclusive education in Ghana. The study employed mixed method approach with the sequential explanatory strategy. The sample population composed of 562 students from six (6) colleges of education in Ghana under one mentor university. The quantitative research approach consisted of 10-item questionnaire which was adapted from the Teachers’ Attitudes towards Inclusive Education (TAIS) scale. Data was collected using both the questionnaire and interview guide. The analysis of quantitative data involved the use of multiple statistical procedures; frequency counts, simple percentages, and standard deviation, while the thematic analysis was used to analyze the qualitative data. The study revealed that pre-service teachers has positive attitude towards the implementation of inclusive education in Ghana. About eighty percent (80.1%) stated that children with special educational needs can be effectively supported to learn in regular classrooms in Ghana (1.30, SD=.64). However, the current regular schools in Ghana cannot accommodate children with special needs education (1.25, SD=.62) due to inadequate space. It is therefore recommended that the government of Ghana and the Ghana Education Service should work together to ensure that there is the availability of adequate facilities in all schools for teachers to effectively implement inclusive education in the new Bachelor of Education (Basic Education) Curriculum
 
 
 
 

Using Random Forest Regression to Determine Influential Force-Time Metrics for Countermovement Jump Height: A Technical Report.

Merrigan, JJ, Stone, JD, Wagle, JP, Hornsby, WG, Ramadan, J, Joseph, M, and Hagen, JA. Using random forest regression to determine influential force-time metrics for countermovement jump height: a technical report. J Strength Cond Res 36(1): 277-283, 2022-The purpose of this study was to indicate the most influential force-time metrics on countermovement jump (CMJ) height using multiple statistical procedures. Eighty-two National Collegiate Athletic Association Division I American football players performed 2 maximal-effort, no arm-swing, CMJs on force plates. The average absolute and relative (i.e., power/body mass) metrics were included as predictor variables, whereas jump height was the dependent variable within regression models (p < 0.05). Best subsets regression (8 metrics, R2 = 0.95) included less metrics compared with stepwise regression (18 metrics, R2 = 0.96), while explaining similar overall variance in jump height (p = 0.083). Random forest regression (RFR) models included 8 metrics, explained ∼93% of jump height variance, and were not significantly different than best subsets regression models (p > 0.05). Players achieved higher CMJs by attaining a deeper, faster, and more forceful countermovement with lower eccentric-to-concentric force ratios. An additional RFR was conducted on metrics scaled to body mass and revealed relative mean and peak concentric power to be the most influential. For exploratory purposes, additional RFR were run for each positional group and suggested that the most influential variables may differ across positions. Thus, developing power output capabilities and providing coaching to improve technique during the countermovement may maximize jump height capabilities. Scientists and practitioners may use best subsets or RFR analyses to help identify which force-time metrics are of interest to reduce the selectable number of multicollinear force-time metrics to monitor. These results may inform their training programs to maximize individual performance capabilities.

Revisiting the declustering of spatial data with preferential sampling

Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data. Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose magnitudes should be close to the respective population values. This paper proposes a resampling method that can compensate for preferential sampling of spatially correlated data without using declustering weights. The application of the method herein generates a dataset of median estimates of quantiles of multiple stratified resamples that is free of preferential sampling. The methodology is illustrated with two examples. The first one involves values actually measured in the field and has the advantage of representing a real scenario of spatial fluctuations and preferential sampling. A second dataset is synthetic and has the main benefit of a priori knowledge of the underlying spatial distribution, thus allowing a satisfactory evaluation of the results against the known baseline. Access to computer code is offered for practical application of the method.

Targeting uncertainty in smart CPS by confidence-based logic

Since Smart Cyber–Physical Systems (sCPS) are complex and decentralized systems of dynamically cooperating components, architecture-based adaptation is of high importance in their design. In this context, a key challenge is that they typically operate in uncertain environments. Thus, an inherent requirement in sCPS design is the need to deal with the uncertainty of data coming from the environment. Existing approaches often rely on the fact that an adequate model of the environment and/or base probabilities or a prior distribution of data are available. In this paper, we present a specific logic (CB logic), which, based on statistical testing, allows specifying transition guards in architecture-based adaptation without requiring knowledge of the base probabilities or prior knowledge about the data distribution. Applicable in state machines’ transition guards in general, CB logic provides a number of operators over time series that simplify the filtering, resampling, and statistics-backed comparisons of time series, making the application of multiple statistical procedures easy for non-experts. The viability of our approach is illustrated on a running example and a case study demonstrating how CB logic simplifies adaptation triggers. Moreover, a library with a Java and C ++ implementation of CB logic’s key operators is available on GitHub.

Pre-service Parents Teachers’ Attitude and Perceived Challenges about Inclusive Education in Ghana: The Ghanaian Inclusive Education Policy

The inclusion of learners with special educational needs into regular schools is a significant pillar in the New B. Ed Basic Education Curriculum for teacher education in Ghana. Based on this, the study aimed at finding the attitude of pre-service parent teachers and their perceived challenges about inclusive education in Ghana. The study employed a convergent mixed method with a sample of 112 sandwich pre-service parent teachers at the Gambaga College of Education. The quantitative research approach consisted 10-item questionnaire scale adapted from the works of Paseka and Schwab (2020) on ‘Parents’ Attitude towards Inclusive Education’ (PAIE) scale. Data was collected using both the questionnaire and focus group discussion. The analysis of quantitative data involved the use of multiple statistical procedures; frequency counts, simple percentages, and standard deviation, while the inductive thematic analysis (ITA) was used to analyse the qualitative data. The findings revealed that the pre-service parent teachers have positive attitude towards inclusive education. They believed that Ghanaian teachers will be able to recognize their children’s strengths and support them with the appropriate contents in inclusive classroom and they can also work well in a good relationship with learners with special educational needs. However, they stressed on some few challenges that may hinder the effective implementation of inclusive education in Ghana. Among the challenges included inadequate resources and the lack of peaceful cooperation among learners in inclusive environment (such as stigmatization). It is therefore recommended that the government and other significant stakeholders ensure that these challenges are remedied for effective implementation of inclusive education in Ghana.

Teachers’ Attributes and Their Students’ Research Productivity

Teachers play a significant role in the intellectual development of students in various techniques, assessments, and methods to improve student skills in school’s subjects. This study therefore, focuses on the effects of research teachers’ personal and professional attributes and their senior high school students’ research productivity. The respondents’ attitudes toward research were also looked into. These were correlated together with the students’ performance in research as evidenced by their outputs. The population of the study is comprised of 11 public and 4 private secondary schools in Cebu City. A total number of 36 research teachers with their corresponding students comprising 111 were selected through purposive sampling techniques. The reliability of the tools using Cronbach Alpha is generated above 0.783, 0.808, and 0.811 which means good and acceptable. Multiple statistical procedures, simple frequency and percentages, weighted means, and descriptive inferential analysis were employed to obtain stronger validity to the study. The results of the study identified that students’ level of research productivity are categorized as “Beginning” and having desirable attitudes towards research. Likewise, teachers have positive attitudes towards doing research and its benefits to their teaching practice and students’ learning process. Using the Pearson r and multiple regressions; the results of the study identify negligible relationship and no significant difference between most of the teacher factors and student research output. However, the teachers’ attitudes are statistically significant in relation to student’s output while the teachers’ output and students’ output have significant difference. Reliable research trainings and providing teaching materials are recommended to address these gaps.

RunData: an easy and intuitive online tool for statistical analyses

RunData is an online tool that requires internet access. This web application is built in R language, which performs multiple statistical procedures in an intuitive, and simple manner. This tool performs Shapiro-Wilk test, analysis of variance (ANOVA), means tests, and regressions. RunData is available at www.rundata.com.br and sistema.rundata.com.br/shiny/app/.

Sifting and winnowing: Analysis of farmer field data for soybean in the US North-Central region

Field trials are commonly used to estimate the effects of different factors on crop yields. In the present study, we followed an alternative approach to identify factors that explain field-to-field yield variation, which consisted of farmer survey data, a spatial framework, and multiple statistical procedures. This approach was used to identify management factors with strongest association with on-farm soybean yield variation in the US North Central (NC) region. Field survey data, including yield and management information, were collected over two crop growing seasons (2014 and 2015) from rainfed and irrigated soybean fields (total of 3568 field-year observations). Fields were grouped into technology extrapolation domains (TEDs) that accounted for soil and climate variation and 9 TEDs were selected based on the number of fields needed to detect yield differences due to management as determined using power analysis. Average yield ranged from 2.5 to 5 Mg ha−1 across TEDs, with field yield distributions in half of the domains having a distributional peak that was close to maximum yields. Conditional inference trees analysis was chosen among 26 statistical procedures as the approach that best combines ability to detect and rank factors (and their interactions) with greatest influence on on-farm yield and relatively easy interpretation of results. Survey data from ca. 150 fields in each of the nine TEDs allowed us to identify key management factors influencing yields for an agricultural area that includes ca. 7 million ha sown with soybean. In five of the nine TEDs, highest yields were observed in early-sown fields. Other factors explaining on-farm yield variation were maturity group, and in-season foliar fungicide and/or insecticide application, but, in some cases, their influence on yield depended upon sowing date and water regime. While the approach proposed here cannot establish cause-effect relationships conclusively, it can certainly provide a focus to replicated field experiments in relation to which management factors to investigate. We believe that future agronomic studies based on farmer survey data can greatly benefit from ex-ante identification of most important TEDs (relative to crop area and production) as well as determination of minimum number of farmer survey data that needs to be collected from each of them based on expected yield differences and variability. The approach is generic enough to be applied in other crop producing regions as long as farmer data and associated climate and soil databases are available.

Different statistical procedures for selection of salt tolerant barley genotypes at germination stage

Growing of salt tolerant crops is a good option to obtain economical yields from saline areas and screening salt tolerant plants, particularly in early growth stages as one of the most important determinants of high yield, is important. So a laboratory experiment was performed to assess several indices for identifying barley genotypes with better performance under saline conditions. The effect of salinity stress was studied through an analysis of the dry matter production, that yielding results showed significant differences among genotypes. The multiple statistical procedures which have been used in this study showed that mean productivity and geometric mean productivity indices could be a useful indicator of desirable genotypes in both stress and non-stress conditions at this stage especially in high level of salinity. The majority of used tolerance indices indicated that MBS8715 was the best barley genotype showing the highest stress resistance for the most salt concentration.

Role of site in the mortality and production of Acacia mangium plantations in Indonesia

In Indonesia, Acacia mangium plantations exceed 1.6 Mha contributing approximately 3.5% of the country’s GDP. The viability of these plantations is increasingly threatened by fungal pathogens, insect pests, squirrels, monkeys, elephants and wind damage. Studies indicate that the problem is growing and in some areas, fungal pathogens such as Ganoderma and Ceratocystis species have contributed up to 50% tree mortality by the fourth rotation. Multiple statistical procedures were employed to examine the influence of soil and topographical properties on tree survival (trees ha−1), wood production (m3 ha−1), and mortality associated with Ganoderma root rot, Ceratocystis wilt and by wind. Soil family level was found to be a good indicator of tree mortality. Plots with fine-loamy Typic Kandiudult soils had the highest tree survival and mortality associated with species of Ganoderma and Ceratocystis, but had the lowest incidence of mortality by wind. The degree of association between soil and topographic variables with tree survival, wood production and the cause of mortality were poor and inconsistent. Tree survival was slightly higher on upslope areas away from valley bottoms, and drier mid-slopes, ridges and hilltops, and very low pH (<3.3) soils. Wood production was also slightly higher in drier, elevated locations, away from valley bottoms. Mortality by wind was slightly higher in moist, poorly drained, low-lying valley bottoms and topographically flat areas. Our ability to further pinpoint the influence of topography and soil attributes on wood production and cause of mortality was greatly compromised by the lack of site-specific soil data, and potential misclassification of the cause of mortality. This study could not reliably or consistently relate tree survival, wood production or the cause of mortality to any one, or combination of, soil and topographic variables.

MULTIPLE TESTING OF SIGN SYMMETRY FOR STOCK RETURN DISTRIBUTIONS

Multiple statistical procedure for testing elliptical model for stock returns distribution is proposed. Sign symmetry conditions are chosen as individual hypotheses for multiple testing. Distribution free uniformly most powerful tests of Neyman structure are constructed for individual hypotheses testing. Associated stepwise multiple testing procedure is applied for the real market data. Numerical experiments shows that hypothesis of elliptical model is rejected. At the same time it is observed that the graph of rejected individual hypotheses has unexpected structure. Namely, this graph is sparse and has a few hubs of high degree. Removing this hubs leads to nonrejection of hypothesis of elliptical model.

Robust identification in random variable networks

A class of distribution free multiple decision statistical procedures is proposed for threshold graph identification in correlation networks. The decision procedures are based on simultaneous application of sign statistics. It is proved that single step, step down Holm and step up Hochberg statistical procedures for threshold graph identification are distribution free in sign similarity network in the class of elliptically contoured distributions. Moreover it is shown that these procedures can be adapted for distribution free threshold graph identification in Pearson correlation network.

Herzberg's Motivation- Hygiene Theory Applied to High School Teachers in Turkey

The authors of this study sought to examine the job satisfaction and motivational level of high school teachers regarding the Hygiene and Motivator factors as identified by Herzberg and to find out the effect of fulfillment of Hygiene and Motivator factors on motivation of high school teachers. A questionnaire titled the quantitative data from Lester’s (1987) TJSQ assessment of teacher job satisfaction and Hoy et al. ’s (1991) OCDQ-RS assessment of school climate were used to collect data for the study. While the data for the study was analyzed using multiple statistical procedures: mean point value, standard deviation, and variance, t-test of significance and One-way-analysis of variance (ANOVA). A paper survey has been distributed to 198 respondents who are all actively involved in high school teaching in Isparta, Turkey. However, Frederick Herzberg's theory which states that what he terms hygiene (job context) factors contribute to dissatisfaction while motivator (job content) factors relate to satisfaction, the study indicates that both hygiene factors and motivation factors contribute to satisfaction and especially, hygiene factors were more satisfying factors in the high school teachers group.

On multivariate network analysis of statistical data sets with different measures of association

The main goal of the present paper is the development of a general framework of multivariate network analysis of statistical data sets. A general method of multivariate network construction, on the basis of measures of association, is proposed. In this paper we consider Pearson correlation network, sign similarity network, Fechner correlation network, Kruskal correlation network, Kendall correlation network, and the Spearman correlation network. The problem of identification of the threshold graph in these networks is discussed. Different multiple decision statistical procedures are proposed. It is shown that a statistical procedure used for threshold graph identification in one network can be efficiently used for any other network. Our approach allows us to obtain statistical procedures with desired properties for any network.

Measures of uncertainty in market network analysis

A general approach to measure statistical uncertainty of different filtration techniques for market network analysis is proposed. Two measures of statistical uncertainty are introduced and discussed. One is based on conditional risk for multiple decision statistical procedures and another one is based on average fraction of errors. It is shown that for some important cases the second measure is a particular case of the first one. The proposed approach is illustrated by numerical evaluation of statistical uncertainty for popular network structures (minimum spanning tree, planar maximally filtered graph, market graph, maximum cliques and maximum independent sets) in the framework of Gaussian network model of stock market.

Statistical procedures for the market graph construction

The statistical analysis of the method of construction of the market graph when considered as a multiple decision statistical procedure is investigated. It is shown that under the condition of additivity of the loss function the method can be optimal in different classes of unbiased multiple statistical procedures. The results are obtained by application of the Lehmann theory of multiple decision procedures to the method of construction of the market graph. The main findings are illustrated by numerical studies of the conditional risk of multiple decision statistical procedures for different loss functions and different return distributions.

Sexual Education: An Intervention and Social Adjustment Programme for Youths in Secondary Education in Nigeria

This study examined the importance of sexuality education as an intervention and social adjustment programme for youth in secondary education in Nigeria. For this purpose, the study sought to find out using three research questions; the importance of sexuality education in secondary education; the extent to which sexuality education served as an intervention and social adjustment programme for youths in secondary education; and the extent to which sexuality education was taught in the curriculum of secondary education. The study being a survey research adopted the descriptive survey research design in order to collect data. A multiple statistical sampling procedure was used in selection of 10% of 5, 926 teachers and 261 public secondary schools within the six education zone in Anambra State. However, the sample of the study constituted 593 teachers from 26 public secondary schools. A questionnaire titled: Sexuality Education Questionnaire for Teachers (SEQT), containing 44 items and drawn on a modified Likert type of 4-point scale was used by the researchers to conduct the study. Validity of the research instrument was carried out by three experts and reliability established using the split half method which yielded a coefficient value of 0.75 using the Pearson Product Moment Correlation Coefficient after the results were collated. Data was analyzed using frequency distribution and the mean at 2.50 rating. Through the findings of the study, recommendations were proffered and among such included: proper enhancement of sexuality education in secondary education curriculum through the provision of effective policy directives; including constant and continuous teachers training, organizing seminars and workshops for teachers in the light of sexuality education.

Modeling the Influence of Nitrogen Rate and Plant Density on Seed Yield, Yield Components and Seed Quality of Safflower

To study the effect of nitrogen rate and plant density at different levels on yield, yield components and quality traits of safflower (cv. Giza 1) an experiment was conducted as split plot design in randomized complete block design arrangement with three replications, during the successive seasons 2010/11 and 2011/12. The factors consisted of four levels of nitrogen (0, 40, 80 and 120 kg N ha -1 ) and four different densities (80,000, 100,000, 133,000 and 200,000 plants ha -1 ). Different statistical analyses such as ANOVA, polynomial regression, correlation, and stepwise multiple linear regression were used. The multiple statistical procedures showed that the main effects of nitrogen rate and plant density levels were significant ( P = 0.01) for yield and yield components studied. A rise in nitrogen rate and plant density increased seed and oil yield, whereas plant height, number of branches plant -1 , number of heads plant

Personal, Situational and Socio-Cultural Factors as Correlates of Intimate Partner Abuse in Nigeria

This study established the relationships between personal, situational and socio-cultural factors and intimate partner abuse among couples in Nigeria. A multiple regression statistical procedure was employed in analyzing the data collected from 200 participants randomly selected from five ministries in Ibadan, Oyo state, Nigeria. Results obtained indicated that the three variables when combined effectively predicted intimate partner abuse (F-ratio of 5.756 significant at 0.05 alpha level). Taken separately, situational and socio-cultural factors contributed significantly to the prediction (t = 2.146, p t = 2.284, p (t = 1.705, p > 0.05). On the basis of these findings it was suggested that counselling psychologists should design intervention strategies to promote life-skills training in schools and out-of-schools settings. These include age-appropriate content on sexuality, conflict resolution, building healthy relationships and personal safety. Also, it was suggested that couples should be informed on the long-term health and social consequences of physical and sexual abuse.