The impact of peer review on the contribution potential of scientific papers

The peer-reviewing process has long been regarded as an indispensable tool in ensuring the quality of a scientific publication. While previous studies have tried to understand the process as a whole, not much effort has been devoted to investigating the determinants and impacts of the content of the peer review itself. This study leverages open data from nearly 5,000 PeerJ publications that were eventually accepted. Using sentiment analysis, Latent Dirichlet Allocation (LDA) topic modeling, mixed linear regression models, and logit regression models, we examine how the peer-reviewing process influences the acceptance timeline and contribution potential of manuscripts, and what modifications were typically made to manuscripts prior to publication. In an open review paradigm, our findings indicate that peer reviewers’ choice to reveal their names in lieu of remaining anonymous may be associated with more positive sentiment in their review, implying possible social pressure from name association. We also conduct a taxonomy of the manuscript modifications during a revision, studying the words added in response to peer reviewer feedback. This study provides insights into the content of peer reviews and the subsequent modifications authors make to their manuscripts.

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FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

Journal of Business Economics ◽

10.35760/eb.2018.v23i1.1812 ◽

2018 ◽

Vol 23 (1) ◽

pp. 60-71

Author(s):

Wigiyanti Masodah

Keyword(s):

Interest Rate ◽

Linear Regression ◽

Interest Rates ◽

Regression Models ◽

Linear Regression Models ◽

Negative Impacts ◽

Main Activity ◽

The Impact ◽

The Given ◽

Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

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Non-Parametric Generalized Additive Models as a Tool for Evaluating Policy Interventions

Mathematics ◽

10.3390/math9040299 ◽

2021 ◽

Vol 9 (4) ◽

pp. 299

Author(s):

Jaime Pinilla ◽

Miguel Negrín

Keyword(s):

Linear Regression ◽

Regression Models ◽

Linear Trend ◽

Generalized Additive Models ◽

Additive Models ◽

Linear Regression Models ◽

Non Linear ◽

Nonlinear Trends ◽

The Impact ◽

Non Parametric

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.

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Impact of foreign direct investment on economic growth in the world during 1975–2015

Scientific Messenger of LNU of Veterinary Medicine and Biotechnology ◽

10.32718/nvlvet9106 ◽

2018 ◽

Vol 20 (91) ◽

pp. 28-32

Author(s):

B. B. Brychka

Keyword(s):

Economic Growth ◽

Literature Review ◽

Regression Models ◽

Trade Openness ◽

Positive Influence ◽

Linear Regression Models ◽

Average Value ◽

Gdp Growth Rate ◽

The World ◽

The Impact

The study is concentrated on examination the impact of FDI on economic growth in the World during 1975–2015. The study consists of four consecutive parts, including introduction, literature review, model and methodology, data, empirical results and conclusion. Each part of the study is focused on its own goals. According to the results of the literature review, there is positive influence of FDI on economic growth in various countries. Economic growth is one of the most important goals of any country. The country image on the international level is dependent on its economic power. Economic growth provides an opportunity to improve the living standards in the country. Most researchers conclude that there is a positive influence of FDI on the countries’ economic growth. However, the impact of FDI is strong in developing countries. Moreover, this relationship is stronger in countries with higher educational and technological level, trade openness and development of the countries’ stock markets. Economists often build regression models to estimate the relationship between the variables. In order to find the impact of FDI on economic growth, we are going to apply linear regression models. We take two variables as indicators of the countries’ economic growth, including current GDP expressed in U.S dollars, and annual GDP growth rate. Taking into account that the World’s GDP in current U.S dollar is a factor variable with the mentioned resulting variables, the regression equation looks as follows: The R-squared of the built model is 0.99, indicating that roughly 100% of changes in the World’s GDP is caused by the chosen factors. As it is seen from the SAS output, the residuals of dependent variable and factors variables are distributed normally among its average value. Thus, non-normality is not observed in the model. Taking into account the coefficients of the factor variables, the log GDP is most sensitive to the changes in trade as a percent of GDP. The log GDP is not quite sensitive to the changes in FDI, since the coefficient of 0.000128 means that increasing of FDI by one unit increase the logarithmic value of GDP by $ 0.000128.

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The effect of leadership style and job motivation on the performance of teachers

JPGI (Jurnal Penelitian Guru Indonesia) ◽

10.29210/021075jpgi0005 ◽

2021 ◽

Vol 6 (2) ◽

pp. 482

Author(s):

Ramsiah Hiranah ◽

Happy Fitria ◽

Achmad Wahidy

Keyword(s):

Leadership Style ◽

Regression Models ◽

Qualitative Data ◽

Teacher Performance ◽

Sampling Technique ◽

Linear Regression Models ◽

Profound Influence ◽

Job Motivation ◽

Study Techniques ◽

The Impact

The main objective of this study is to define and explain the impact on teacher performance of the leadership style of the head of the Madrasah and job motivation simultaneously. Quantitative analysis is this form of study performed in this study. Techniques for qualitative data collection, questionnaires and documentation..“ Using different linear regression models, it was analyzed. With the help of the version 21 SPSS program. A saturated sampling technique was used in this analysis, where all 49 respondents were tested. From the following conclusions, the findings of data processing and interpretation are drawn: The principal's leadership style has a positive and important effect on the performance of teachers. Motivation for work has a positive and meaningful influence on the success of teachers. At the same time, the leadership style of madrasah principals and job motivation have a profound influence on teacher performance.

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Evaluation of determinants of the serological response to the split-inactivated influenza vaccine

10.1101/2021.10.07.21264416 ◽

2021 ◽

Author(s):

Shaohuan Wu ◽

Ted M. Ross ◽

Michael A. Carlock ◽

Elodie Ghedin ◽

Hyungwon Choi ◽

...

Keyword(s):

Influenza Vaccine ◽

Regression Models ◽

Seasonal Influenza ◽

Vaccine Dose ◽

Serological Response ◽

Linear Regression Models ◽

Negative Effects ◽

Categorical Response ◽

One Year ◽

The Impact

AbstractThe seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from >1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, prevaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for >75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the strongest determinants on seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants, and an effect of vaccination month. BMI played a surprisingly small role, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.

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The Impact of the Community Built Environment on the Walking Times of Residents in a Community in the Downtown Area of Fuzhou

Sustainability ◽

10.3390/su11030691 ◽

2019 ◽

Vol 11 (3) ◽

pp. 691

Author(s):

Lizhen Zhao ◽

Zhenjiang Shen ◽

Yanji Zhang ◽

Yan Ma

Keyword(s):

Built Environment ◽

Regression Models ◽

Education Level ◽

Linear Regression Models ◽

Downtown Area ◽

Point Of Interest ◽

Independent Variable ◽

And Gender ◽

The Impact ◽

Walking Time

By means of on-site and network investigation, we collected data relevant to residents of communities, point of interest (POI) data, and land-use data of Fuzhou. We set traffic walking time and leisure walking time as an independent variable, built environment as dependent variable, and gender, age, education level and income level as control variables. Six linear regression models were established using Statistical Product and Service Solutions (SPSS). The results showed that in the 5D (i.e., Density, Diversity, Design, Destination and Distance) elements of the built environment, the density was negatively correlated with the traffic walking time, whereas other elements were positively correlated with the walking time, but the degree of influence was different.

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Medication Intake Is Associated with Lower Plasma Carotenoids and Higher Fat-Soluble Vitamins in the Cross-Sectional MARK-AGE Study in Older Individuals

Journal of Clinical Medicine ◽

10.3390/jcm9072072 ◽

2020 ◽

Vol 9 (7) ◽

pp. 2072

Author(s):

Daniela Weber ◽

Bastian Kochlik ◽

Wolfgang Stuetz ◽

Martijn E. T. Dollé ◽

Eugène H. J. M. Jansen ◽

...

Keyword(s):

Regression Models ◽

Plasma Concentrations ◽

Older Individuals ◽

Linear Regression Models ◽

Cross Sectional ◽

Medication Intake ◽

The One ◽

Fat Soluble Vitamins ◽

The Impact ◽

Β Carotene

The regular use of medication may interfere with micronutrient metabolism on several levels, such as absorption, turnover rate, and tissue distribution, and this might be amplified during aging. This study evaluates the impact of self-reported medication intake on plasma micronutrients in the MARK-AGE Project, a cross-sectional observational study in 2217 subjects (age- and sex-stratified) aged 35–75 years from six European countries that were grouped according to age. Polypharmacy as possible determinant of micronutrient concentrations was assessed using multiple linear regression models adjusted for age-group, dietary fruit, vegetables, and juice intake, and other confounders. Younger participants reported taking fewer drugs than older participants. Inverse associations between medication intake and lutein (−3.31% difference per increase in medication group), β-carotene (−11.44%), α-carotene (−8.50%) and positive associations with retinol (+2.26%), α-tocopherol/cholesterol (+2.89%) and γ-tocopherol/cholesterol (+1.36%) occurred in multiple adjusted regression models. Combined usage of a higher number of medical drugs was associated with poorer status of carotenoids on the one hand and higher plasma concentrations of retinol, α- and γ-tocopherol on the other hand. Our results raise concerns regarding the safety of drug combinations via the significant and surprisingly multifaceted disturbance of the concentrations of relevant micronutrients.

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The impact of strategy on public sector set-aside programs: the case of the state of Ohio

Journal of Public Procurement ◽

10.1108/jopp-03-2018-003 ◽

2018 ◽

Vol 18 (1) ◽

pp. 31-49 ◽

Cited By ~ 1

Author(s):

Ian Y. Blount ◽

Jay Seetharaman ◽

Trevor L. Brown

Keyword(s):

Program Implementation ◽

Regression Models ◽

Implementation Strategy ◽

State Level ◽

The State ◽

State Agencies ◽

Linear Regression Models ◽

Content Type ◽

Program Strategy ◽

The Impact

Purpose The purpose of this study is to examine the impact of program strategy on the implementation of the efficacy of a procurement set-aside program at the state level. Design/methodology/approach This study examines the impact of program implementation strategy across two administrations considering the most compelling alternative arguments for what drives agency purchasing through contracts with MBEs. Findings The results of mixed effects linear regression models on the procurement expenditures of 70 state agencies in Ohio from 2008-2015 show significantly higher rates of procurement expenditures with MBEs under the Kasich administration. Originality/value These results provide support for the argument that changes in program implementation strategy led to substantive increases in the use of MBEs by state agencies in Ohio.

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A Streamlined Workflow for Conversion, Peer-Review and Publication of Omics Metadata as Omics Data Papers

10.20944/preprints202009.0357.v1 ◽

2020 ◽

Author(s):

Mariya Dimitrova ◽

Raïssa Meyer ◽

Pier Luigi Buttigieg ◽

Teodor Georgiev ◽

Georgi Zhelezov ◽

...

Keyword(s):

Peer Review ◽

Open Data ◽

Scientific Data ◽

Quality Data ◽

Data Publishing ◽

Academic Publishing ◽

Omics Data ◽

High Quality ◽

Data Interoperability ◽

The Impact

Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer-review and increases the impact of datasets by enhancing their visibility, accessibility, and re-usability. We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivise researchers to publish high-quality data sets, we created a workflow for streamlined import of omics metadata directly into a data paper manuscript. An omics data paper template was designed by defining key article sections which encourage the description of omics datasets and methodologies. The workflow was based on REpresentational State Transfer services and Xpath to extract information from the European Nucleotide Archive, ArrayExpress and BioSamples databases, which follow community-agreed standards. The workflow for automatic import of standard-compliant metadata into an omics data paper manuscript facilitates the authoring process. It demonstrates the importance and potential of creating machine-readable and standard-compliant metadata. The omics data paper structure and workflow to import omics metadata improves the data publishing landscape by providing a novel mechanism for creating high-quality, enhanced metadata records, peer reviewing and publishing of these. It constitutes a powerful addition for distribution, visibility, reproducibility and re-usability of scientific data. We hope that streamlined metadata re-use for scholarly publishing encourages authors to improve the quality of their metadata to achieve a truly FAIR data world.

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Diversification Strategy and Financial Performance of Nigeria Private Firms

International Journal of Scientific Research and Management ◽

10.18535/ijsrm/v8i07.em02 ◽

2020 ◽

Vol 8 (07) ◽

pp. 1883-1889

Author(s):

Ada Mac- Ozigbo ◽

Dr. Cross Ogohi Daniel

Keyword(s):

Firm Performance ◽

Financial Crisis ◽

Regression Models ◽

Global Financial Crisis ◽

Private Firms ◽

Linear Regression Models ◽

Her Family ◽

Diversified Firms ◽

The Impact ◽

Better Than

The relationship between diversification and firm performance varies among institutions and over time. Less is known about the advantageousness of diversification in economy-wide crises, which have occurred frequently in recent years Using data from a recent survey, we studied nearly 400 Nigeria private firms using two different approaches panel and cross-period comparisons. The findings of both approaches show that diversified firms performed better than focused firms. This was also true during the 2008 global financial crisis. The higher the diversification level, the more positive the firm performance was. We also investigated the influence of ownership structure. Firms that are totally owned by the founding owner and his/her family tend to have unsatisfactory performance under crisis. This finding provides evidence of the increasing attention on management and governance to explain firm. Linear regression models were evaluated to test the effect of diversification on firm performance. Panel A uses profit as the dependent variable, and Panel B uses sales. For each year (2007, 2008, and 2009), two regression models were evaluated: one testing the impact of diversification and the other testing the impact of the diversification level. We found that diversified firms performed better than focused firms during the recent global financial crisis. The diversification level was positively and linearly related to performance, that is, more diversified firms performed better. Moreover, we found that private firms that are totally owned by the founding owner and his/her family performed worse under crisis.

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