scholarly journals Forecasting COVID-19 cases and deaths in epidemic-mitigating European countries by Richards function-based regression analyses

2020 ◽  
Author(s):  
XINMIAO FU
Keyword(s):  
Regression Analysis ◽  
European Countries ◽  
Regression Analyses ◽  
Richards Function

The COVID-19 pandemic has hit many countries, and in some European countries it has been mitigated since April. Here we applied Richards function to simulate and forecast the course of COVID-19 epidemics in Italy, Spain, France, Germany, Turkey, Belgium, Ireland, Netherlands, Portugal and Switzerland. Potential total COVID-19 confirmed cases in these countries were estimated to be 240400±1300, 294100±4000, 178500±800, 176900±700, 155400±1000, 57900±400, 24000±200, 46200±300, 30000±300 and 30700±100 respectively. Most of these countries are predicted to approach ending stage between late May and early June such that daily new cases will become minimal, which may guide societal and economic restorations. In addition, total COVID-19 deaths were estimated to be 33500±300, 28200±200, 27800±200, 8740±80, 4500±30, 9250±70, 1530±20, 6240±50, 1380±10 and 1960±8, respectively. To our best knowledge, this is the first study forecasting the COVID-19 epidemic by applying the Richard function-based regression analysis.

scholarly journals School Satisfaction and Happiness in 10-Year-Old Children from Seven European Countries

Children ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 370
Author(s):  
Diego Gómez-Baya ◽  
Francisco José García-Moro ◽  
Alicia Muñoz-Silva ◽  
Nuria Martín-Romero
Keyword(s):  
Correlation Analysis ◽  
Student Teachers ◽  
Life Experience ◽  
School Satisfaction ◽  
European Countries ◽  
Student Experiences ◽  
Regression Analyses ◽  
School Life ◽  
Healthy Functioning ◽  
Contextual Indicators

School satisfaction is conceptualized as a crucial factor influencing children´s happiness and consequent healthy functioning in multiple developmental areas. Research to date has mainly evaluated how contextual factors related to the interactions between the student, teachers and classmates influence children’s happiness, not considering other important factors more related to their own student experiences. The aim of the present study was to examine the effect of school satisfaction on happiness in 10-year-old children from Europe. Children’s global school satisfaction levels, as well as different separate indicators of school satisfaction (i.e., satisfaction with other children in class; school marks; school life experience as a student; things they have learned; and relationships with teachers) were considered. The study comprised a sample of 7.445 10-year-old children from seven European countries. First, correlation analysis showed that the overall school satisfaction measure, as well as its different indicators, had positive associations with happiness levels. Second, regression analyses confirmed the effect by indicators of global school satisfaction on happiness. The indicators with the strongest effects were the satisfaction with their life as a student and the satisfaction with other children in the class, while the smallest effects were found regarding the satisfaction with the relationships with teachers and the things learned. These results point out the need to consider personal and contextual indicators of school satisfaction in a program design to foster happiness in 10-year-old children.

THE EVALUATION OF SELF-MONITORING ATTRIBUTES

1991 ◽  
Vol 19 (3) ◽  
pp. 205-215 ◽  
Author(s):  
Arts Jiujias ◽  
Peter Horvath
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Regression Analyses ◽  
Self Monitoring

Eighty-six Canadian female undergraduates attributed self-monitoring traits to a target presented on videotape, and evaluated her in terms of liking. Attributed self-monitoring was negatively correlated with attraction to the target and was the only predictor of attraction in a multiple regression analysis. Multiple regression analyses with subscales of attributed self-monitoring as predictors suggested that the evaluations may be the result of the attributed unpredictability of the high self-monitoring prototype.

DECISION MAKING BY VARIABLE CONTRIBUTION IN DISCRIMINANT, LOGIT, AND REGRESSION ANALYSES

2004 ◽  
Vol 03 (02) ◽  
pp. 265-279 ◽  
Author(s):  
STAN LIPOVETSKY ◽  
MICHAEL CONKLIN
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Statistical Models ◽  
Regression Analyses ◽  
Discriminant Functions ◽  
Multivariate Statistical ◽  
Linear Discriminant ◽  
Variable Contribution ◽  
Linear Aggregate

Comparative contribution of predictors in multivariate statistical models is widely used for decision making on the importance of the variables for the aims of analysis and prediction. However, the analysis can be made difficult because of the predictors' multicollinearity that distorts estimates for coefficients in the linear aggregate. To solve the problem of the robust evaluation of the predictors' contribution, we apply the Shapley Value regression analysis that provides consistent results in the presence of multicollinearity both for regression and discriminant functions. We also show how the linear discriminant function can be constructed as a multiple regression, and how the logistic regression can be approximated by linear regression that helps to obtain the variables contribution in the linear aggregate.

Identification and Validation of a Seven m6A-related lncRNAs Signature Predicting Prognosis of Ovarian Cancer

2021 ◽  
Author(s):  
Yan Li ◽  
Xiaoying Wang ◽  
Yue Han ◽  
Xun Li
Keyword(s):  
Ovarian Cancer ◽  
Regression Analysis ◽  
Correlation Analysis ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Pearson Correlation ◽  
Regression Analyses ◽  
Cox Regression Analysis ◽  
Pearson Correlation Analysis

Abstract Background: Long non-coding RNAs (lncRNAs) play an important role in angiogenesis, immune response, inflammatory response and tumor development and metastasis. m6 A (N6 - methyladenosine) is one of the most common RNA modifications in eukaryotes. The aim of our research was to investigate the potential prognostic value of m6A-related lncRNAs in ovarian cancer (OC).Methods: The data we need for our research was downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Pearson correlation analysis between 21 m6A regulators and lncRNAs was performed to identify m6A-related lncRNAs. Univariate Cox regression analysis was implemented to screen for lncRNAs with prognostic value. A least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analyses was used to further reduct the lncRNAs with prognostic value and construct a m6A-related lncRNAs signature for predicting the prognosis of OC patients. Results: 275 m6A-related lncRNAs were obtained using pearson correlation analysis. 29 m6A-related lncRNAs with prognostic value was selected through univariate Cox regression analysis. Then, a seven m6A-related lncRNAs signature was identified by LASSO Cox regression. Each patient obtained a riskscore through multivariate Cox regression analyses and the patients were classified into high-and low-risk group using the median riskscore as a cutoff. Kaplan-Meier curve revealed that the patients in high-risk group have poor outcome. The receiver operating characteristic curve revealed that the predictive potential of the m6A-related lncRNAs signature for OC was powerful. The predictive potential of the m6A-related lncRNAs signature was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the m6A-related lncRNAs signature was an independent prognostic factor for OC patients. Moreover, a nomogram based on the expression level of the seven m6A-related lncRNAs was established to predict survival rate of patients with OC. Finally, a competing endogenous RNA (ceRNA) network associated with the seven m6A-related lncRNAs was constructed to understand the possible mechanisms of the m6A-related lncRNAs involed in the progression of OC.Conclusions: In conclusion, our research revealed that the m6A-related lncRNAs may affect the prognosis of OC patients and identified a seven m6A-related lncRNAs signature to predict the prognosis of OC patients.

The alternative negative constructions in spoken and written Korean: Logistic regression analysis

2019 ◽  
Vol 15 (2) ◽  
pp. 419-442
Author(s):  
Beom-mo Kang
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Mixed Effects ◽  
Written Language ◽  
Regression Analyses ◽  
Relevant Factor ◽  
Factors Influencing ◽  
Frequency Of Use ◽  
Relevant Factors

AbstractAdopting quantitative corpus-based methods, this paper focuses on the alternative negative constructions in Korean, [anV] and [Vanhda]. Logistic regression analyses for a mixed-effects model were carried out on data drawn from the Sejong Korean Corpus. Certain features of the verb or adjective in negative constructions significantly affect the use of the two negative constructions. A relevant factor is register/medium (spoken or written), among other significant interactions of factors. Furthermore, the fact that frequency is consistent with other relevant factors, together with certain diachronic facts of Korean, supports the claim that frequency of use plays an important role in linguistic changes. Another finding is that, notwithstanding noticeable differences between spoken and written language, the factors influencing the use of the two negative constructions in Korean are largely similar in the spoken and written registers.

scholarly journals Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110414
Author(s):  
Xiaoyong Li ◽  
Jiaqong Lin ◽  
Yuguo pan ◽  
Peng Cui ◽  
Jintang Xia
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
Regression Analyses ◽  
Related Gene ◽  
Cox Regression Analysis

Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.

scholarly journals International Tourism and Outbreak of Coronavirus (COVID-19): A Cross-Country Analysis

2020 ◽  
pp. 004728752093159 ◽  
Author(s):  
Mohammad Reza Farzanegan ◽  
Hassan F. Gholipour ◽  
Mehdi Feizi ◽  
Robin Nunkoo ◽  
Amir Eslami Andargoli
Keyword(s):  
Regression Analysis ◽  
Effect Size ◽  
Statistical Significance ◽  
International Tourism ◽  
Regression Analyses ◽  
Socioeconomic Determinants ◽  
Country Analysis ◽  
High Flows ◽  
Cross Country ◽  
The Relationship

This study examines the relationship between international tourism and COVID-19 cases and associated deaths in more than 90 nations. We use a cross-country regression analysis and find a positive correlation between international tourism and the cumulated level of COVID-19 confirmed cases and death by April 30, 2020. Our regression analyses show that countries exposed to high flows of international tourism are more prone to cases and deaths caused by the COVID-19 outbreak. This association is robust even after controlling for other socioeconomic determinants of COVID-19 outbreak and regional dummies. Based on our estimations, a 1% higher level of inbound and outbound tourism is associated with 1.2% and 1.4% higher levels of confirmed COVID-19 cases and death, respectively, controlling for other factors. When we normalize the number of cases and death by size of population, the statistical significance remains robust, especially for the COVID-19 deaths, while the effect size reduces.

The Relationship between HR Expenditure and Firm's Performance: Case of S&P BSE SENSEX 30 Companies

2017 ◽  
Vol 9 (3) ◽  
pp. 59
Author(s):  
Gaurav Talan ◽  
Kanchan Sehrawat ◽  
Gagan Deep Sharma
Keyword(s):  
Regression Analysis ◽  
Financial Performance ◽  
Competitive Advantage ◽  
Management Practices ◽  
Business Environment ◽  
Regression Analyses ◽  
Hr Management ◽  
Indian Company ◽  
The Relationship ◽  
Positive Effect

<p>In today’s dynamic business environment, for companies to exist, they must continuously look for areas for improvement and gain competitive advantage. It therefore becomes quintessential for companies to know which factors can have a positive effect on the company’s performance. The purpose of this article is thus to explore if there a relationship between the HR expenses of an Indian company and its financial performance and is this impact positive enough to motivate these companies to augment such efforts in improving the HR management practices. For, this purpose, data on expenditure on human resource and profit after tax (PAT) for BSE- SENSEX 30 companies was extracted for the period of10 years. In order to test the hypothesis of this study, correlation and regression analyses were performed. Results of correlation revealed that HR expenditures are positively related to Firms performance. The findings from regression analysis revealed that HR expenditure have statistically significant effect on a firm’s financial performance.</p>

Rainfastness of Insecticide Deposits on Loblolly Pine Foliage and the Efficacy of Adjuvants in Preventing Washoff

1991 ◽  
Vol 26 (2) ◽  
pp. 287-298 ◽  
Author(s):  
John C. Nord ◽  
William D. Pepper
Keyword(s):  
Regression Analysis ◽  
Linear Relationship ◽  
Confidence Intervals ◽  
Loblolly Pine ◽  
Significant Relationship ◽  
Rainfall Amount ◽  
Regression Analyses ◽  
Significant Linear Relationship ◽  
Wettable Powder ◽  
Percent Mortality

The rainfastness of several insecticides on loblolly pine foliage was determined by using a laboratory rain chamber and by testing the foliage in bioassays with adult leaffooted pine seed bugs, Leptoglossus corculus (Say). The efficacy of eight commercial and two experimental adjuvants in preventing rainwashing of deposits of azinphosmethyl and phosmet from loblolly pine foliage was also determined. Deposits of azinphosmethyl from 0.2% (Al) simulated sprays made from emulsifiable concentrates (EC's), (Guthion 2S and 2L), were highly susceptible to rainwashing. Regression analysis of these data showed a significant linear relationship between arcsin percent mortality and rainfall amount in cm [y = 68.08 – 6.88/(Rainfall)]. Using the confidence intervals from the regression analysis, it was estimated that rainfall in excess of 1.42 cm would reduce mean seed bug mortality on treated foliage to an amount below 80% with 95% confidence, and likewise, rainfall in excess of 3.95 cm would reduce mean mortality to an amount below 50%. However, mortality of L. corculus on deposits of simulated azinphosmethyl 0.2% (Al) sprays made from the wettable powder (Guthion 50 WP) were virtually unaffected by 15 cm of rain. Spray deposits from permethrin (Pounce 3.2EC) at lower rates were moderately to highly resistant to rainwashing. Regression analyses perfomed on these data showed no significant relationship between mortality and rainfall amount. Most of the adjuvants were ineffective in preventing rainwashing of deposits of azinphosmethyl (EC) or phosmet (WP). Only two, Bio-Film and Exhalt 800, showed any promise.

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