The Research on the Influencing Factors of Students' Advanced Mathematics Score Based on Hierarchical Multiple Regression Model

2021 ◽  
Author(s):  
Bin Wang ◽  
Yong MingYao
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Influencing Factors ◽  
Multiple Regression Model ◽  
Advanced Mathematics ◽  
Hierarchical Multiple Regression ◽  
Mathematics Score

scholarly journals What explains wage differences between male and female Brazilian physicians? A cross-sectional nationwide study

BMJ Open ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. e023811 ◽  
Author(s):  
Giulia Marcelino Mainardi ◽  
Alex J Flores Cassenote ◽  
Aline G Alves Guilloux ◽  
Bruno A Miotto ◽  
Mario Cesar Scheffer
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Multiple Regression Model ◽  
Work Characteristics ◽  
Office Work ◽  
Wage Differences ◽  
Cross Sectional ◽  
Hierarchical Multiple Regression ◽  
Male And Female ◽  
Wage Difference

ObjectiveIn many countries an increase in the number of women in medicine is accompanied by gender inequality in various aspects of professional practice. Women in medical workforce usually earn less than their male counterparts. The aim of this study was to describe the gender wage difference and analyse the associated factors in relation to Brazil’s physicians.Participants2400 physicians.SettingNationwide, cross-sectional study conducted in 2014.MethodsData were collected via a telephone enquiry. Sociodemographic and work characteristics were considered factors, and monthly wages (only the monthly earnings based on a medical profession) were considered as the primary outcome. A hierarchical multiple regression model was used to study the factors related to wage differences between male and female physicians. The adjustment of different models was verified by indicators of residual deviance and the Akaike information criterion. Analysis of variance was used to verify the equality hypothesis subsequently among the different models.ResultsThe probability of men receiving the highest monthly wage range is higher than women for all factors. Almost 80% of women are concentrated in the three lowest wage categories, while 51% of men are in the three highest categories. Among physicians working between 20 and 40 hours a week, only 2.7% of women reported receiving >US$10 762 per month, compared with 13% of men. After adjustment for work characteristics in the hierarchical multiple regression model, the gender variable estimations (ß) remained, with no significant modifications. The final effect of this full model suggests that the probability of men receiving the highest salary level (≥US$10 762) is 17.1%, and for women it is 4.1%. Results indicate that a significant gender wage difference exists in Brazil.ConclusionThe inequality between sexes persisted even after adjusting for working factors such as weekly workload, number of weekly on-call shifts, physician office work, length of practice and specialisation.

scholarly journals Resilience mediates the effect of self-efficacy on symptoms of prenatal anxiety among pregnant women: a nationwide smartphone cross-sectional study in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ruqing Ma ◽  
Fengzhi Yang ◽  
Lijuan Zhang ◽  
Kristin K. Sznajder ◽  
Changqing Zou ◽  
...  
Keyword(s):  
Regression Model ◽  
Pregnant Women ◽  
Multiple Regression ◽  
Self Efficacy ◽  
Cross Sectional Study ◽  
Multiple Regression Model ◽  
Sectional Study ◽  
Cross Sectional ◽  
Hierarchical Multiple Regression ◽  
Prenatal Anxiety

Abstract Background Prenatal anxiety is one of the most prevalent mental disorders during pregnancy. This study assessed the prevalence of prenatal anxiety and examined whether resilience could play the mediating role in the association between self-efficacy and symptoms of prenatal anxiety among pregnant women in China. Methods A nationwide smartphone cross-sectional study was carried out in three cities (Shenyang of Liaoning Province, Zhengzhou of Henan Province and Chongqing Municipality) in China from July 2018 to July 2019. The questionnaire consisted of questions on demographic characteristics, the Generalized Anxiety Disorder Scale (GAD-7), the Chinese version of General Self-efficacy Scale (GSES), and the 14-item Wagnild and Young Resilience Scale (RS-14). A total of 665 pregnant women were recruited in this study. A hierarchical multiple regression model was employed to explore the associate factors and mediators of symptoms of prenatal anxiety. A structural equation model was employed to test the hypothesis that resilience mediates the association between self-efficacy and symptoms of prenatal anxiety. Results The prevalence of symptoms of prenatal anxiety was 36.4% in this study. Self-efficacy was negatively correlated with symptoms of prenatal anxiety (r = -0.366, P < 0.01). Resilience had a significant positive correlation with self-efficacy (r = 0.612, P < 0.01) and had a negative correlation with symptoms of prenatal anxiety (r = -0.427, P < 0.01). The hierarchical multiple regression model indicated that self-efficacy and resilience were the main factors associated with symptoms of prenatal anxiety and contributed to 11.9% and 6.3% to the variance of symptoms of prenatal anxiety, respectively. Resilience served as a mediator between self-efficacy and symptoms of prenatal anxiety (a*b = -0.198, Bias-corrected and accelerated bootstrap 95% Confidence interval: -0.270, -0.126). Conclusions Self-efficacy was a negative predictor of symptoms of prenatal anxiety among pregnant women. Moreover, resilience mediated the relation between self-efficacy and symptoms of prenatal anxiety among pregnant women in China. It was observed in this study that psychological interventions might be beneficial for pregnant women to relieve symptoms of prenatal anxiety through improved self-efficacy and resilience.

Factors Affecting NPAs in Indian Banking Sector

Paradigm ◽  
2021 ◽  
Vol 25 (2) ◽  
pp. 181-193
Author(s):  
Nitya Garg
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Banking Sector ◽  
Relative Weight ◽  
Multiple Regression Model ◽  
Factors Affecting ◽  
Weight Analysis ◽  
Specific Factors ◽  
Relative Weight Analysis ◽  
Bank Specific Factors

Banking sector is the backbone of any economy, so it is necessary to focus on its performance which is largely affected by its non-performing assets (NPAs). In the year 2018–2019, NPA of scheduled banks was Rs 355,076 Crore which is 3.7% of net advances. The purpose of this study is to identify the determinants based on analysis from previous literatures, and majorly macroeconomic and bank specific factors which are affecting NPAs using the relative weight analysis and to frame a model to predict future NPAs using multiple regression model using SPSS. The study also attempts to focus on actions and remedies that banks should make to control future NPAs. Findings of the study will act as a scaffolding for financial analysts and policymakers to prevent the conversion of its performing assets into NPAs and also help in proper management of banks and also in the recovery of economy.

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