Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments

2013 ◽  
Vol 480 ◽  
pp. 33-45 ◽  
Author(s):  
Axel Ritter ◽  
Rafael Muñoz-Carpena
Keyword(s):  
Performance Evaluation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Hydrological Models

A validation of the performance management scale

2018 ◽  
Vol 35 (6) ◽  
pp. 1253-1267 ◽  
Author(s):  
Khahan Na-nan ◽  
Kanokporn Chaiprasit ◽  
Peerapong Pukkeeree
Keyword(s):  
Factor Analysis ◽  
Performance Evaluation ◽  
Performance Management ◽  
Goodness Of Fit ◽  
Mean Square ◽  
Evaluation Performance ◽  
Content Type ◽  
Performance Review ◽  
And Performance ◽  
Fit Index

Purpose The purpose of this paper is to develop a performance management (PM) scale questionnaire that encompasses the pre-requisite, performance planning, performance evaluation, performance review, and performance application dimensions of PM. Design/methodology/approach In the study, the 33 questionnaire questions were first validated using exploratory factor analysis (EFA) and then by confirmatory factor analysis (CFA) along the three performance dimensions. The research sample consists of 330 entrepreneurs. The factor analysis results confirm the validity of the questionnaire as a reliable entrepreneur PM evaluation tool, as evidenced by the composite reliability of 0.845 and the average variance extracted of 0.532. Findings All constructs revealed the acceptable internal consistency reliability. A good model fit was found for the measurement model using several fit index like χ2=449.983, degree of freedom=415, p-value (p)=0.114, goodness of fit index=0.927, adjusted goodness of fit index=0.901, root mean square error of approximation=0.016, and root of mean square residuals=0.032. Research limitations/implications The PM model was examined using EFA and CFA only. A sample with only SMEs entrepreneurs and large sample size and sample area can be used in future research. Practical implications This research paper is an endeavor to explore only the reliability and validity of the PM model. Thus all the five dimension, namely “pre-requisite” “performance planning,” “performance evaluation,” “performance review,” and “performance application” proved out of be reliable and validated when it will be tested in case of SMEs’ high-growth sectors and high-impact sectors. Originality/value The main contribution of this research is that all factors have a good fit and acceptable reliability value; each factor can be measured individually depending on the nature of the research.

Adoption of mobile banking services

2019 ◽  
Vol 37 (5) ◽  
pp. 1165-1189 ◽  
Author(s):  
Apostolos Giovanis ◽  
Pinelopi Athanasopoulou ◽  
Costas Assimakopoulos ◽  
Christos Sarmaniotis
Keyword(s):  
Theory Of Planned Behavior ◽  
Technology Acceptance ◽  
Planned Behavior ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Explanatory Power ◽  
Equation Modeling ◽  
Mobile Banking ◽  
Content Type

PurposeThe purpose of this paper is to investigate which of four well-established theoretical models (i.e. technology acceptance model, theory of planned behavior, unified theory of acceptance and use of technology, decomposed theory of planned behavior (DTPB)) best explains potential users’ behavioral intentions to adopt mobile banking (MB) services.Design/methodology/approachDrawing on data from 931 potential users in Greece, the structural equation modeling method was used to examine and compare the four models in goodness-of-fit, explanatory power and statistical significance of path coefficients.FindingsResults indicate that the best model is an extension of the DTPB with perceived risk (PR). Customers’ attitude, determined by three rationally-evaluated MB attributes (usefulness, easiness and compatibility), is the main driver of consumers’ intentions to adopt MB services. Additionally, consumers’ perceptions of availability of knowledge, resources and opportunities necessary for using the service, and the pressure of interpersonal and external social contexts toward the use of MB are the other two, less important, adoption drivers. Finally, PR negatively affects attitude formation and inhibits willingness to use MB services.Practical implicationsFindings can help marketers of financial institutions to select the more parsimonious model to develop appropriate marketing strategies to increase adoption rates of MB services.Originality/valueThis is the first study that compares the performance of four well-known innovation adoption models to explain consumers’ behavior in the MB context.

A STATISTICAL METHODOLOGY TO SIMPLIFY SOFTWARE METRIC MODELS CONSTRUCTED USING INCOMPLETE DATA SAMPLES

2007 ◽  
Vol 17 (06) ◽  
pp. 689-707 ◽  
Author(s):  
VICTOR K. Y. CHAN ◽  
W. ERIC WONG ◽  
T. F. XIE
Keyword(s):  
Incomplete Data ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Statistical Hypothesis ◽  
Software Project ◽  
Statistical Hypothesis Testing ◽  
Work Effort ◽  
K Nearest Neighbors ◽  
Quality Metric ◽  
Software Metric

Software metric models predict the target software metric(s), e.g., the development work effort or defect rates, for any future software project based on the project's predictor software metric(s), e.g., the project team size. Obviously, the construction of such a software metric model makes use of a data sample of such metrics from analogous past projects. However, incomplete data often appear in such data samples. Moreover, the decision on whether a particular predictor metric should be included is most likely based on an intuitive or experience-based assumption that the predictor metric has an impact on the target metric with a statistical significance. However, this assumption is usually not verifiable "retrospectively" after the model is constructed, leading to redundant predictor metric(s) and/or unnecessary predictor metric complexity. To solve all these problems, we derived a methodology consisting of the k-nearest neighbors (k-NN) imputation method, statistical hypothesis testing, and a "goodness-of-fit" criterion. This methodology was tested on software effort metric models and software quality metric models, the latter usually suffers from far more serious incomplete data. This paper documents this methodology and the tests on these two types of software metric models.

Structural Equation Modeling: An Alternative to Traditional Validation Techniques

1986 ◽  
Vol 14 (4) ◽  
pp. 345-352
Author(s):  
Margaret E. Bell ◽  
Jean A. Massey
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Equation Modeling ◽  
Fit Indices ◽  
T Values ◽  
Conditions Of Learning ◽  
Nursing Course ◽  
Cardiovascular Nursing

Validation of the sequencing of objectives is an important step in structural design. Prior statistical techniques, such as the reproducibility coefficient, have yielded only summary information. In contrast, structural equation modeling provides both goodness-of-fit indices and effect coefficients for links or paths between time-ordered events, i.e., objectives. Discussed here is the application of structural equation modeling to a set of objectives in a senior-level cardiovascular nursing course. Consistent with the theory-based requirement of structural equation modeling, the objectives were developed using Robert Gagné's conditions of learning. Also discussed is the use of “t” values, which indicate statistical significance of the paths, for testing instructional links in the learning model.

scholarly journals Effect of Grandmother-Mother Relationship on Grandmother-Grandchildren Ties: Focusing on the Mediating Effect of Coparenting

2020 ◽  
Vol 58 (2) ◽  
pp. 149-161
Author(s):  
Hye Jeong Choi ◽  
Jeong Shin An
Keyword(s):  
Indirect Effect ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Equation Model ◽  
Mediating Effect ◽  
Mediation Effect ◽  
Likelihood Method ◽  
Chi Square ◽  
Fit Index

This study showed that the association between grandmother-mother relationship and grandmother-grandchildren ties is mediated by the coparenting. Participants consisted of 329 grandmothers who were rearing preschool aged grandchildren in the Seoul and Gyeonggido area. SPSS 23.0 performed descriptive statistical analysis and correlation analysis. The structural equation model was estimated with AMOS 23.0. Parameters were estimated using the maximum likelihood method. Model fit index used the chi-square statistic, the goodness of fit index (GFI), the Turker-Lewis index (TLI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA). The mediation effect analysis followed a two-step verification process; direct and indirect effect. In addition, statistical significance of the indirect effect was examined using a bootstrapping procedure. The results are as follows. First, a positive correlation was found between the grandmother-mother relationship, grandmother-grandchildren ties, and coparenting. Second, the association between grandmother-mother relationship and grandmother-grandchildren ties is mediated by coparenting. The results of this study suggest that the quality of the grandmother’s relationship with mothers and cooperative coparenting is important to building relationships with grandchildren. In addition, coparenting can be an important mechanism for grandmother-mother relationships and grandmother-grandchild ties. Based on the results of this study, we discussed ways to improve the grandmothers’ relationship quality with the mother and strengthen parenting ability.

scholarly journals Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China

2016 ◽  
Author(s):  
Chao Wang ◽  
Shuang Li ◽  
Tao Li ◽  
Shanfa Yu ◽  
Junming Dai ◽  
...  
Keyword(s):  
Occupational Stress ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Well Being ◽  
Equation Model ◽  
Hunan Province ◽  
Electronic Manufacturing ◽  
Proposed Model

Background: This study aimed to identify the association between occupational stress and depression-well-being by proposing a comprehensive and flexible job burden-capital model with its corresponding hypotheses. Methods: For this research, 1618 valid samples were gathered from the electronic manufacturing service industry in Hunan Province, China; self-rated questionnaires were administered to participants for data collection after obtaining their written consent. The proposed model was fitted and tested through structural equation model analysis. Results: Single-factor correlation analysis results indicated that coefficients between all items and dimensions had statistical significance. The final model demonstrated satisfactory global goodness of fit (CMIN/DF=5.37, AGFI=0.915, NNFI=0.945, IFI=0.952, RMSEA=0.052). Both the measurement and structural models showed acceptable path loadings. Job burden and capital were directly associated with depression and well-being or indirectly related to them through personality. Multi-group structural equation model analyses indicated general applicability of the proposed model to basic features of such a population. Gender, marriage and education led to differences in the relation between occupational stress and health outcomes. Conclusions: The job burden-capital model of occupational stress-depression and well-being was found to be more systematic and comprehensive than previous models.

scholarly journals Time-saving Effects Using Helicopter Transportation: Comparison to a Ground Transportation Time Predicted Using a Social Navigation Software

2021 ◽  
Author(s):  
Ji Young Jang ◽  
Jang Hun Kim
Keyword(s):  
Open Source ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Navigation Systems ◽  
Time Saving ◽  
Social Navigation ◽  
Transportation Time ◽  
Ground Ambulance ◽  
Time Required ◽  
Navigation Software

Abstract IntroductionPrevious comparison studies regarding two types of transportation, helicopter (HEMS) versus ground emergency medical services (GEMS), have shown underlying heterogeneity as these options have completely different routes and consequent times with reference to one patient. To compare the two types of transportation on a case-by-case basis, we analyzed the retrospectively reviewed HEMS and predicted GEMS data using an open-source navigation software.MethodsPatients transferred by military HEMS from 2016 to 2019 were retrospectively enrolled. The HEMS records on the time of notification, injury point and destination address, and time required were reviewed. The GEMS data on distance and the predicted time required were acquired using open-source social navigation systems. Comparison analyses between the two types of transportation were conducted. Further, linear logistic regression analyses were performed on the distance and time of the two options.ResultsA total of 183 patients were enrolled. There was no statistical difference (p=0.3021) in the distance between the two types of transportation, and the HEMS time was significantly shorter than that of GEMS (61.31 vs. 116.92 minutes, p<0.001). The simple linear curves for HEMS and GEMS were separately secured, and two graphs presented the statistical significance (p) as well as reasonable goodness-of-fit (R2). In general, the HEMS graph demonstrates a more gradual slope and narrow distribution compared to that of GEMS. ConclusionIdeally, HEMS is identified as a better transportation modality because it has a shorter transportation time (56 minutes saved) and a low possibility of potential time delays (larger R2).Running tileHelicopter vs. navigation-based ground ambulance

scholarly journals 3510 Academic influence in gynecologic oncology is associated with industry funding: an analysis of the Open Payments database

2019 ◽  
Vol 3 (s1) ◽  
pp. 32-32
Author(s):  
David Samuel ◽  
Shelby Adler ◽  
Nicole Vilardo ◽  
Gregory Gressel
Keyword(s):  
Goodness Of Fit ◽  
Statistical Significance ◽  
Gynecologic Oncology ◽  
Academic Rank ◽  
Online Database ◽  
Industry Funding ◽  
H Index ◽  
Fit Testing ◽  
Academic Influence ◽  
Open Payments

OBJECTIVES/SPECIFIC AIMS: Industry payments to physicians can present a conflict of interest. The Physician Payments Sunshine Act mandates the disclosure of these financial relationships to increase transparency. Recent studies in other surgical specialties have shown that research productivity is associated with greater industry funding. In this study, we characterize the relationship between academic influence and industry funding among academic gynecologic oncologists. METHODS/STUDY POPULATION: Departmental websites were used to identify academic gynecologist oncologists and their demographic information. The Hirsch index (h-index) relates an author’s number of publications to number of times referenced by other publications, a validated measure of an author’s academic influence. This was obtained from the Scopus database. The Center for Medicaid and Medicare Services Open Payments online database was searched for all industry payments in 2017. The NIH Reporter online database was searched for active grants. Goodness of fit testing showed that all variables followed nonparametric distributions. Medians were compared using Mann-Whitney U tests and Kruskal-Wallis analysis of variance with post-hoc Dunn’s test. RESULTS/ANTICIPATED RESULTS: Four hundred and sixty-six academic gynecologic oncologists were included in the analysis. In 2017, 89.7% of this group received industry funding totaling $41.4 million. Median industry funding was $453 [IQR $67-19684] and median h-index was 14 [IQR 8-26]. Only 8.1% of gynecologic oncologists were NIH grant recipients and they received significantly higher industry payments ($357 vs. 11,168, P<0.01). Gender and academic rank were not associated with industry funding. Gynecologic oncologists in the highest decile of industry funding received a median payment of $447,651[N=46, IQR $285,770 – 896,310] totaling $36.5 million. The median h-index for this top-earning decile was 23 [N=46, IQR 16.5-30.3]. When stratified by payment amount, median h index increased but only reached statistical significance in the highest cohort receiving >$100,000 (N = 63, P<0.05). DISCUSSION/SIGNIFICANCE OF IMPACT: The majority of academic gynecologic oncologists receive industry funding although there are large variations in payments. Those receiving the largest payments are more likely to hold NIH grants and have greater academic influence.

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