scholarly journals Historical and cross-disciplinary trends in the biological and social sciences reveal an accelerating adoption of advanced analytics

2020 ◽  
Author(s):  
Taylor Bolt ◽  
Jason S. Nomi ◽  
Danilo Bzdok ◽  
Lucina Q. Uddin
Keyword(s):  
Social Sciences ◽  
Research Methods ◽  
Structural Equation ◽  
Quantitative Methods ◽  
Data Driven ◽  
Survival Models ◽  
Equation Modeling ◽  
Learning Approaches ◽  
Scientific Publications ◽  
The Past

AbstractMethods for data analysis in the biomedical, life and social sciences are developing at a rapid pace. At the same time, there is increasing concern that education in quantitative methods is failing to adequately prepare students for contemporary research. These trends have led to calls for educational reform to undergraduate and graduate quantitative research method curricula. We argue that such reform should be based on data-driven insights into within- and cross-disciplinary use of research methods. Our survey of peer-reviewed literature screened ∼3.5 million openly available research articles to monitor the cross-disciplinary usage of research methods in the past decade. We applied data-driven text-mining analyses to the methods and materials section of a large subset of this corpus to identify method trends shared across disciplines, as well as those unique to each discipline. As a whole, usage of T-test, analysis of variance, and other classical regression-based methods has declined in the published literature over the past 10 years. Machine-learning approaches, such as artificial neural networks, have seen a significant increase in the total share of scientific publications. We find unique groupings of research methods associated with each biomedical, life and social science discipline, such as the use of structural equation modeling in psychology, survival models in oncology, and manifold learning in ecology. We discuss the implications of these findings for education in statistics and research methods, as well as within- and cross-disciplinary collaboration.

scholarly journals Educating the future generation of researchers: A cross-disciplinary survey of trends in analysis methods

PLoS Biology ◽  
2021 ◽  
Vol 19 (7) ◽  
pp. e3001313
Author(s):  
Taylor Bolt ◽  
Jason S. Nomi ◽  
Danilo Bzdok ◽  
Lucina Q. Uddin
Keyword(s):  
Structural Equation ◽  
Quantitative Methods ◽  
Social Science Research ◽  
Data Driven ◽  
Research Articles ◽  
Survival Models ◽  
Equation Modeling ◽  
Learning Approaches ◽  
Scientific Publications ◽  
Analytic Methods

Methods for data analysis in the biomedical, life, and social (BLS) sciences are developing at a rapid pace. At the same time, there is increasing concern that education in quantitative methods is failing to adequately prepare students for contemporary research. These trends have led to calls for educational reform to undergraduate and graduate quantitative research method curricula. We argue that such reform should be based on data-driven insights into within- and cross-disciplinary use of analytic methods. Our survey of peer-reviewed literature analyzed approximately 1.3 million openly available research articles to monitor the cross-disciplinary mentions of analytic methods in the past decade. We applied data-driven text mining analyses to the “Methods” and “Results” sections of a large subset of this corpus to identify trends in analytic method mentions shared across disciplines, as well as those unique to each discipline. We found that the t test, analysis of variance (ANOVA), linear regression, chi-squared test, and other classical statistical methods have been and remain the most mentioned analytic methods in biomedical, life science, and social science research articles. However, mentions of these methods have declined as a percentage of the published literature between 2009 and 2020. On the other hand, multivariate statistical and machine learning approaches, such as artificial neural networks (ANNs), have seen a significant increase in the total share of scientific publications. We also found unique groupings of analytic methods associated with each BLS science discipline, such as the use of structural equation modeling (SEM) in psychology, survival models in oncology, and manifold learning in ecology. We discuss the implications of these findings for education in statistics and research methods, as well as within- and cross-disciplinary collaboration.

scholarly journals Condition 9 and 10 Tests of Model Confirmation: A Review of James, Mulaik, and Brett (1982) and Contemporary Alternatives

2017 ◽  
Vol 23 (1) ◽  
pp. 6-29 ◽  
Author(s):  
Larry J. Williams ◽  
Ernest H. O’Boyle ◽  
Jia (Joya) Yu
Keyword(s):  
Social Sciences ◽  
Factor Analysis ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Unique Contribution ◽  
New Techniques ◽  
The Past ◽  
The Social ◽  
Current Article

Structural equation modeling (SEM) serves as one of the most important advances in the social sciences in the past 40 years. Through a combination of factor analysis and path analysis, SEM allows organizational researchers to test causal models while accounting for random and nonrandom (bias) measurement error. SEM is now one of the most commonly used analytic techniques and its modern day ubiquity can be traced in large part to a series of intellectual contributions by Larry James. The current article focuses on the seminal work, James, Mulaik, and Brett (1982), and the unique contribution of the “conditions” required for appropriate confirmatory inference with the path and latent variable models. We discuss the importance of James et al.’s Condition 9 and 10 tests, systematically review 14 years of studies using SEM in leading management journals and reanalyze results based on new techniques that extend James et al. (1982), and conclude with suggestions for improved Condition 9 and 10 assessments.

scholarly journals Latent Variable Structural Equation Modeling: A Flexible Tool for Establishing Validity and More

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Drew Altschul
Keyword(s):  
Social Sciences ◽  
Structural Equation Modeling ◽  
Construct Validity ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Statistical Techniques ◽  
Flexible Tool ◽  
The Past

Petrinovich highlighted many salient issues in the behavioral and social sciences that are of concern to this day, such as insufficient attention to construct validity. Structural equation modeling, particularly with regard to latent variables, is introduced and discussed in this context. Though conceptual issues remain, analytic and statistical techniques have made immense strides in the past three decades since the article was written, and properly used, offer solutions to many problems Petrinovich identified.

CONSUMER DECISION MODEL (CDM) ANALYSIS OF EFFECTIVENESS VIDEOTRON ADVERTISING SERVED IN SURAKARTA

ProBank ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 69-81
Author(s):  
Muhammad Khoiruman ◽  
Ambar Warniati
Keyword(s):  
Purchase Intention ◽  
Structural Equation ◽  
Decision Model ◽  
Equation Modeling ◽  
Scientific Publications ◽  
Consumer Decision ◽  
Intention To Purchase ◽  
Brand Recognition ◽  
Level Of Confidence ◽  
The Government

This study aims to analyze the effectiveness of Videotron media ads served in Surakarta using the Consumer Decision Model (CDM) Analysis. Viewed ad serving costs in videtron large enough it is necessary to study the effectiveness of the ads served on videtron. The model that is used in measuring the effectiveness of an ad in this research is the Consumer Decision Model (CDM). The research objective was to determine the effect the message of the ad (Information), branding (Brand Recognition), the formation of an attitude (Attitude), the level of confidence in the message (Confidence), and intention to purchase (Intention) market target after seeing ad impressions through Videotron. The study population is a society in Surakarta with sampling method is purposive sampling of 200 respondents Data analysis technique using Structural Equation Modeling (SEM) which resulted in the conclusion that the message of the ad (Information) positive effect but not significant with branding (Brand Recognition), formation attitude (attitude), and the level of confidence in the message (confidence). Brand recognition is positive and significant impact on the confidence and attitude while confidence and attitude positive and significant effect on the intention to purchase (Intention) market target after seeing ad impressions through Videotron. Outcomes of this study are: enrichment of teaching materials, especially marketing management, Scientific publications (national journals) and an input for an advertiser, the advertising company and the Government of Surakarta about the effectiveness of the ads served through Videotron so they can be a policy in the future.Keywords: Videotron, advertising, Consumer Decision Model, Information, Brand Recognition, Attitude, Confidence, and Intention

Is lodging research suffering from methods bias? An assessment of published research during 1990-2016

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Faizan Ali ◽  
Mehmet Ali Koseoglu ◽  
Fevzi Okumus ◽  
Eka Diraksa Putra ◽  
Mehmet Yildiz ◽  
...  
Keyword(s):  
Structural Equation ◽  
Quantitative Methods ◽  
Empirical Studies ◽  
Secondary Data ◽  
Equation Modeling ◽  
Content Type ◽  
Data Collection And Analysis ◽  
Hospitality And Tourism ◽  
Method Bias ◽  
Published Research

Purpose The study aims to investigate if lodging research suffers from a method bias by comprehensively reviewing the research methodology used in lodging related research articles. Design/methodology/approach In all, 2,647 published papers in 16 leading hospitality and tourism published between 1990 and 2016 are analyzed using bibliometric technique. Findings In all, 69% of the empirical studies in lodging research across 26 years period used quantitative methods, with an increasing reliance on regression-based analysis and structural equation modeling, a disturbing plunging trend in methods diversity. Findings also suggest an increasing trend of using secondary data. Research limitations/implications Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided. Originality/value This is the first study that reviewed a large corpus of published research (2,647 papers in 16 hospitality and tourism journals from the last 27 years) to highlight (a) methodology used, (b) methods employed and (c) data collection and analysis procedures.

scholarly journals The Influence of Leadership Style, Competency and Compensation on Employee Performance and Its Impact on Organizational Performance in Kementerian Pertanian

FOCUS ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 28-42
Author(s):  
Sugito Efendi ◽  
Suwardi Suwardi
Keyword(s):  
Organizational Performance ◽  
Leadership Style ◽  
Structural Equation ◽  
Research Method ◽  
Quantitative Methods ◽  
Employee Performance ◽  
Equation Modeling ◽  
Survey Method ◽  
Directorate General ◽  
The Impact

This study aims to analyze the influence of leadership style, competence, compensation on employee performance and the impact on organizational performance on the employees of the Directorate General of Agricultural Infrastructure and Facilities. This study used a survey method by distributing questionnaires to employees of the Directorate General of Agricultural Infrastructure and Facilities. As the respondent. This research method uses quantitative methods with technical analysis of Structural Equation Modeling (SEM) with the AMOS version 22 application. The research sample used in this study were 158 respondents. The results showed that leadership style, competence and compensation directly had a positive and significant effect on employee performance. Leadership style, competence and compensation directly have a positive and significant effect on organizational performance. Leadership style, competence and compensation indirectly have a positive and significant effect on organizational performance through employee performance.

scholarly journals The Effect of Distributive Justice, Procedural Justice of Compensation and Emotional Intelligence on Affective Commitments

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Nur Rizqi Febriandika
Keyword(s):  
Emotional Intelligence ◽  
Distributive Justice ◽  
Procedural Justice ◽  
Structural Equation ◽  
Quantitative Methods ◽  
Affective Commitment ◽  
Equation Modeling ◽  
Significant Positive Effect ◽  
Managerial Employees ◽  
Positive Effect

This research determines the distributive justice of compensation, procedural justice of compensation and emotional intelligence on affective commitment. The populations of this study are 115 non-managerial employees of three BMT in Yogyakarta. This study uses quantitative methods and SEM (Structural Equation Modeling) is used to analyze the data collection which is operationalized by the AMOS 21 application program. The results of this study indicate that distributive justice and emotional intelligence have a significant positive effect on affective commitment while procedural justice compensation has no effect on affective commitment.

scholarly journals The role of supply chain management on Indonesian small and medium enterprise competitiveness and performance

2022 ◽  
Vol 10 (1) ◽  
pp. 109-116 ◽  
Author(s):  
Hwihanus Hwihanus ◽  
Oscarius Yudhi Ari Wijaya ◽  
Diah Rani Nartasari
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Competitive Advantage ◽  
Significant Influence ◽  
Structural Equation ◽  
Quantitative Methods ◽  
Sample Selection ◽  
Equation Modeling ◽  
Company Performance ◽  
Chain Management

The purpose of this study is to analyze the effect of supply chain management on competitive advantage in SMEs, the effect of competitive advantage on company performance in SMEs, and the influence of supply chain management on company performance mediated by competitive advantage in SMEs. This study uses quantitative methods and data analysis techniques based on Structural Equation Modeling using SmartPLS 3.0 software. The sample selection method uses non-probability sampling methods. Online questionnaires were sent to 340 SMEs respondents, the next step is to evaluate the returned 320 questionnaires. The results indicate that supply chain management had a significant influence on company performance and competitive advantage. Competitive Advantage also had a significant influence on company performance and played a mediate influence between supply chain management and company performance. The company's ability had a positive effect on competitive advantage and finally, adequate company capabilities had an impact on competitive advantage.

scholarly journals The influence of social media marketing, product innovation and market orientation on Indonesian SMEs marketing performance

2022 ◽  
Vol 6 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Khamaludin Khamaludin ◽  
Syahriani Syam ◽  
Febri Rismaningsih ◽  
Lusiani Lusiani ◽  
Lily Arlianti ◽  
...  
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Market Orientation ◽  
Product Innovation ◽  
Structural Equation ◽  
Quantitative Methods ◽  
Social Media Marketing ◽  
Equation Modeling ◽  
Snowball Sampling ◽  
Marketing Performance

The purpose of this study is to analyze the influence of social media marketing, product innovation, market orientation on marketing performance. The study uses quantitative methods and data analysis techniques are based on Structural Equation Modeling using SmartPLS 3.0 software. The sample selection method uses the snowball sampling method. Online questionnaires are sent to 320 SMEs in Banten Province, where 300 responses are used. The results of data analysis show that social media marketing has a significant effect on marketing performance, product innovation has a significant effect on marketing performance and market orientation has a significant effect on marketing performance.

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